Freelance and remote Data engineers jobs

Build and maintain scalable data pipelines and reusable datasets in a Databricks lakehouse environment to support reporting, visualization, machine learning and data-driven decision-making across finance, sales, supply chain, marketing and other business functions. Key responsibilities include: Develop and maintain scalable data pipelines and data products. Ingest, validate, clean and transform structured and unstructured data using Python, PySpark and SQL. Build data models and reporting datasets for Tableau and other analytics tools. Integrate existing data warehouses and reporting systems with modern cloud analytics platforms. Improve pipeline reliability, data quality and processing performance. Implement automated testing, monitoring, documentation and CI/CD practices. Collaborate with analysts, architects, developers and business stakeholders to deliver effective data solutions. Provide technical guidance, conduct code reviews and mentor other data engineers. Requirements At least 7 years of data engineering experience, including developing and supporting production data pipelines. Strong SQL skills and knowledge of data modelling, database design and data warehousing. Hands-on experience with Databricks, Apache Spark and cloud data platforms. Strong proficiency in Python and PySpark. Experience developing ETL/ELT pipelines and integrating data from multiple source systems. Experience creating reliable datasets for Tableau or comparable business intelligence tools. Familiarity with source control, automated testing and CI/CD practices. Ability to troubleshoot complex data issues and optimise pipeline performance. Strong communication and collaboration skills, with experience working with technical teams and business stakeholders. Preferred Experience and Qualifications Experience with Spotfire, Oracle, Informatica, R or data virtualisation. Databricks certification. Read more

We are seeking an experienced Data Engineer to design, develop, and support enterprise data solutions. The role will focus on data engineering, modeling, integration, quality, warehousing, governance, analytics, business intelligence, and data science initiatives. The successful candidate will work with modern Microsoft Azure, Informatica, Snowflake, and related data technologies to deliver scalable and reliable data platforms. They will also collaborate with technical teams, business stakeholders, and senior leadership to translate complex data and technical concepts into clear, actionable insights. This role requires a proactive, adaptable, and strategic professional who can identify opportunities for improvement, make informed decisions, manage competing priorities, and contribute to a positive and inclusive work environment. Requirements Bachelor’s degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related quantitative field. At least 8 years of experience in data engineering or a closely related data-focused discipline. Experience with data modeling, ETL/ELT, data integration, master data or entity management, data quality, data warehousing, analytics, business intelligence, data science, and data governance. Proficiency in programming and query languages, including C, Python, SQL, and Java. Experience with Microsoft data technologies, including SQL Server, Synapse, Cosmos DB, HDInsight, Azure Data Factory, Azure Databricks, Power BI, and Microsoft Fabric. Experience with Informatica Cloud technologies, such as Cloud Integration Hub, Data Integration Hub, Cloud Data Governance and Catalog, Master Data Management, and Data Quality. Experience with Snowflake and other leading industry data platforms. Strong written and verbal communication skills, including the ability to communicate effectively with senior leadership and both technical and non-technical audiences. Ability to simplify and explain complex technical information in a clear, engaging, and memorable manner. Strong critical-thinking, creative problem-solving, research, analytical, and decision-making skills. Ability to identify trends in complex data, assess short- and long-term impacts, advise decision-makers, and influence stakeholders through effective persuasion and negotiation. Proactive and innovative approach, with a focus on continuous improvement, efficiency, strategic thinking, and delivering a strong client experience. Ability to adapt to changing circumstances, manage multiple workstreams, respond to unexpected issues, and balance short- and long-term priorities. Demonstrated respect for diverse backgrounds, perspectives, and working styles, with strong interpersonal awareness and collaboration skills. Positive, resilient, and professional approach to challenging situations, conflict resolution, and difficult conversations. Commitment to knowledge sharing, stakeholder engagement, and building a strong professional reputation. Additional Information Location: Remote role supporting Chicago, Illinois; local candidates are highly preferred. Employment Type: W2 only. Work Authorization: Any authorization accepted except H1B and CPT. Engagement Restrictions: C2C, 1099, and third-party profiles are not accepted. Read more

Cruz Street is seeking a hands-on Data Engineer for a contract-to-hire role supporting client data solutions and the development of DashProphet 2.0, its AI-enabled SaaS analytics product. The role begins at approximately 20 hours per week, with a potential path to full-time employment as the company grows. The successful candidate will build production-grade data pipelines across AWS and Azure, develop analytics-ready data models, support embedded and multi-tenant analytics, and prepare data foundations for AI and data science applications. Key responsibilities include: Building integrations with REST APIs, SFTP, databases, and files, including authentication, pagination, rate limiting, and incremental loading. Developing S3-based lake and lakehouse architectures using raw, staged, and curated data zones, Parquet or Iceberg, and the Glue Data Catalog. Creating ETL and ELT pipelines in Python and PySpark using AWS Glue and Azure Data Factory. Developing dimensional data models, stored procedures, and optimized queries in Amazon Redshift and Azure Synapse, with ad hoc access through Athena. Building QuickSight datasets and dashboards, including SPICE and row-level security for multi-tenant environments. Orchestrating workflows with Step Functions, EventBridge, Lambda, and related monitoring, alerting, and data quality controls. Preparing data pipelines and features for AI applications using services such as Amazon Bedrock, SageMaker, embeddings, and vector stores. Contributing to infrastructure-as-code and CI/CD using tools such as CDK, CloudFormation, Terraform, GitHub Actions, and CodePipeline. Troubleshooting production issues and conducting root cause analysis. Participating in client requirements sessions, estimating work, and producing clear technical documentation. The role will support client solutions across multiple industries, embedded analytics, the DashProphet 2.0 product, Cruz Street’s Context Warehouse and QuickSight Hub offerings, AI and data science initiatives, and reusable data engineering accelerators. Requirements Required Qualifications At least five years of AWS data engineering experience. At least five years of Python data engineering experience. At least five years of experience designing and building advanced data solutions, including APIs, SFTP, AWS Glue, Azure Data Factory, data lakes, lakehouses, warehouses, and relational databases. Strong SQL skills, including analytical data modeling and query optimization. At least one year of experience planning, building, deploying, and maintaining agentic AI applications. Working knowledge of Git, CI/CD, and collaborative software development. Strong written and verbal communication skills. Comfort working directly with clients and participating in requirements discussions. Ability to work on a 1099 contract basis for approximately 20 hours per week. Ability to commute to Vero Beach, Florida for in-person collaboration. Preferred Qualifications Five or more years of Azure data engineering experience. AWS or Azure certifications in solutions architecture, DevOps, data engineering, or AI and machine learning. Experience with Bedrock, SageMaker, OpenSearch vector search, Azure OpenAI, Azure AI Search, RAG, embeddings, and vector databases. Experience building multi-tenant SaaS data platforms or embedded analytics solutions. Experience with Apache Iceberg, Lake Formation, open table formats, and data governance. Consulting or client-facing delivery experience. Experience working with regulated data, such as HIPAA-protected information, and applying data security best practices. Additional Information Compensation and Benefits Contract rate starting at $75 per hour, negotiable based on experience and fit. Approximately 20 expected hours per week at the start. Potential full-time conversion with a starting salary of $115,000 plus healthcare, paid time off, and a 401(k). Flexible schedule. Professional development assistance. Support for AWS certifications and training. Work Arrangement Hybrid remote position based in Vero Beach, Florida 32960. In-person collaboration at Cruz Street’s headquarters, with the remainder of work performed remotely and on a deliverable basis. Application Information Applicants should submit a resume and a short description of an end-to-end data pipeline they have built, including the data sources, services used, and outcome. Applicants should also provide AWS or Azure certification IDs or Credly links. Applicants may be asked whether they have built and deployed an agentic AI application in production and to briefly describe that application and an end-to-end data pipeline. About Cruz Street Cruz Street is a data engineering, analytics, business intelligence, AI, data science, and enterprise software company headquartered in Vero Beach, Florida. Founded in New York in 2018, the company is an AWS QuickSight Service Delivery Partner serving clients across industries including media and advertising, healthcare and life sciences, SaaS, financial services, retail, and professional organizations. Cruz Street is an equal opportunity employer and welcomes applicants of all backgrounds. The company does not discriminate on the basis of any protected characteristic. Read more

This is a remote Data Engineer position within the Data & AI practice, focused on building modern data platforms for clients using Microsoft Azure, Microsoft Fabric, and Azure Databricks. The role involves designing, developing, and maintaining scalable data infrastructure that enables reliable access to analytics-ready data and supports business intelligence, reporting, and AI applications. The successful candidate will work with architects, data scientists, analysts, engineers, and client stakeholders to ingest, clean, transform, govern, and deliver trusted data. Design, build, and deploy scalable batch and streaming data pipelines from diverse data sources. Ingest and transform structured, semi-structured, and unstructured data from databases, APIs, files, and event streams. Develop analytics-ready datasets using Microsoft Fabric, Azure Data Factory, Azure Databricks, ADLS Gen2, OneLake, and Delta Lake. Apply Medallion architecture patterns across Bronze, Silver, and Gold data layers. Build and consume APIs and reusable data services for reporting, applications, and downstream analytics. Implement data quality checks, validation rules, governance standards, security controls, and monitoring. Monitor, troubleshoot, and optimize data pipelines and systems for performance, reliability, accuracy, and security. Collaborate with data scientists, analysts, architects, engineers, and client stakeholders to translate data requirements into technical solutions. Document data flows, architectures, models, transformation logic, and technical processes. Participate in code reviews and agile delivery activities, including sprint planning, stand-ups, and estimation. Support data activation for operational systems and emerging Data Agent and Copilot-style use cases. Requirements 1–3 years of professional experience in data engineering or a related hands-on technical role; relevant internships and academic projects may be considered for entry-level candidates. Strong proficiency in Python and SQL, with experience writing production-quality code. Hands-on experience with PySpark and an understanding of distributed data processing. Experience or exposure to Microsoft Azure data technologies, including Azure Data Factory, Microsoft Fabric, ADLS Gen2, and/or Azure Databricks. Knowledge of Delta Lake and Unity Catalog is advantageous. Understanding of ETL/ELT processes and the end-to-end data lifecycle from ingestion through activation. Knowledge of dimensional, normalized, and star-schema data modeling and data warehousing principles. Experience building or consuming APIs for data integration. Familiarity with Git and basic CI/CD practices; Azure DevOps experience is a plus. Understanding of data security, access control, governance, Microsoft Purview, and role-based access principles. Strong analytical, troubleshooting, and problem-solving skills, with close attention to data quality and accuracy. Ability to communicate effectively with technical colleagues and client stakeholders. Relevant certifications, such as Microsoft Azure Data Engineer Associate, are desirable but not required. Additional Information This is a remote position. Read more

We are seeking an experienced Data Engineer to design, develop, and support modern data solutions across data engineering, integration, warehousing, analytics, business intelligence, data science, governance, data quality, and master data management. The role will involve working with Microsoft Azure, Informatica, Snowflake, and other leading data technologies to build scalable data pipelines, models, platforms, and analytics solutions. The successful candidate will collaborate with technical teams, business stakeholders, and senior leadership to translate complex data and technical concepts into clear, actionable insights. The Data Engineer will be expected to apply critical and creative thinking, identify trends and opportunities in complex data, recommend solutions, and support both short-term priorities and long-term business objectives. The role also requires a proactive, adaptable, strategic, and continuously improvement-focused approach. Requirements Bachelor’s degree in computer science, data science, software engineering, information systems, or a related quantitative field. At least 8 years of overall data engineering experience. Strong experience with data modeling, ETL/ELT, data integration, master data and entity management, data quality, data warehousing, analytics, business intelligence, data science, and data governance. Proficiency in programming and database languages such as C, Python, SQL, and Java. Experience with Microsoft technologies, including SQL Server, Synapse, Cosmos DB, HDInsight, Azure Data Factory, Azure Databricks, Power BI, and Microsoft Fabric. Experience with Informatica Cloud technologies, including CIH, DIH, CDGC, Master Data Management, and Data Quality. Experience with Snowflake and other leading industry data platforms. Excellent written and verbal communication skills, including the ability to communicate effectively with senior leadership and diverse technical and non-technical audiences. Ability to simplify and explain complex technical information in a clear, concise, and engaging manner. Strong critical-thinking, analytical, research, problem-solving, persuasion, and negotiation skills. Ability to recognize trends, evaluate business implications, make timely decisions, and advise key stakeholders. Proactive and innovative approach, with a focus on identifying solutions, improving processes, increasing efficiency, and contributing ideas for continuous improvement. Ability to manage multiple priorities, adapt to changing circumstances, and balance short-term needs with long-term objectives. Demonstrated respect for diverse perspectives, emotional intelligence, collaboration, humility, and professionalism. Ability to remain positive, resilient, composed, and constructive when handling conflict or challenging situations. Commitment to knowledge sharing, stakeholder engagement, and building a strong professional reputation. Additional Information Location: Remote role based in or near Chicago, Illinois; local candidates are highly preferred. Employment Type: W2 only. Work Authorization: Any authorization accepted, except H-1B and CPT. Engagement Restrictions: C2C, 1099, and third-party profiles are not accepted. Read more

Design, build, and continuously improve the client’s online platform. Research, recommend, and implement technology solutions in line with industry best practices and standards. Take ownership of the resilience, reliability, and availability of assigned products. Contribute effectively as a collaborative and productive member of the team. Requirements Senior Data Engineer with strong expertise in knowledge graph technologies and semantic data engineering. Knowledge Graphs and Knowledge Graph Architecture Neo4j and Cypher RDF, RDF triples, and triple stores SPARQL Ontology Engineering and OWL Semantic Modeling and Graph Data Modeling Semantic Web and Linked Data Employment Details and Benefits Fixed-term employment contract Work-life balance Flexible working arrangements What GeekSoft Consulting Offers International and collaborative consulting culture Clear career development opportunities Comprehensive Dutch benefits package focused on well-being, mobility, and career growth Read more

We are seeking a Data Engineer to design, develop, and support data engineering solutions across data modeling, ETL/ELT, data integration, master data and entity management, data quality, data warehousing, analytics, business intelligence, data science, and data governance. The role involves working with modern Microsoft Azure, Informatica, Snowflake, and other industry-leading data technologies. The successful candidate will translate complex technical information for technical and non-technical audiences, identify insights from complex data, advise decision-makers, and contribute to strategic business and client outcomes. The Data Engineer will demonstrate initiative, innovation, adaptability, sound judgment, and a commitment to continuous improvement. The role also requires effective collaboration with stakeholders, clear communication with senior leadership, and the ability to build trust through respectful, positive, and resilient interactions. Requirements Bachelor’s degree in computer science, data science, software engineering, information systems, or a related quantitative field. At least 8 years of overall data engineering experience. Experience with data modeling, ETL/ELT, data integration, master data management, entity management, data quality, data warehousing, predictive and prescriptive analytics, business intelligence, data science, and data governance. Proficiency in C, Python, SQL, and Java. Experience with Microsoft technologies, including SQL Server in IaaS and PaaS environments, Azure Synapse, Cosmos DB, HDInsight, Azure Data Factory, Azure Databricks, Power BI, and Microsoft Fabric. Experience with Informatica cloud technologies, including CIH, DIH, CDGC, Master Data Management, and Data Quality. Experience with Snowflake and other relevant industry-leading data platforms. Strong written and verbal communication skills, including the ability to communicate credibly and confidently with senior leadership. Ability to simplify and explain complex technical information to diverse technical and non-technical audiences. Strong critical-thinking, creative problem-solving, research, analytical, decision-making, persuasion, and negotiation skills. Ability to recognize trends in complex data and assess both short- and long-term business implications. Proactive, strategic, innovative, and solutions-oriented approach to work. Ability to manage multiple priorities, adapt to changing circumstances, and balance short- and long-term objectives. Demonstrated respect for diverse backgrounds, perspectives, and working styles. Positive, resilient, and professional approach to collaboration, conflict resolution, and challenging situations. Commitment to knowledge sharing, continuous improvement, stakeholder engagement, and developing a strong professional presence. Additional Information Location: Remote; Chicago, Illinois. Employment type: W2 only. Work authorization: Any authorization accepted; H1B and CPT candidates are not eligible. Location preference: Local Chicago-area candidates highly preferred. Recruiting restrictions: No C2C, 1099, or third-party profiles accepted. Read more

We are seeking a Senior Azure Data Engineer with Databricks expertise to design, develop, optimize, and maintain scalable cloud-based data solutions for analytics and enterprise data platforms. The role will involve developing and optimizing SQL Server and Azure SQL databases, writing advanced T-SQL queries and database objects, implementing indexing and performance-tuning strategies, and ensuring database security, integrity, and reliability. The successful candidate will work with Azure SQL Database, Databricks, Apache Spark, Delta Lake, Spark SQL, PySpark, and SQL to support large-scale data processing, transformations, analytics, and hybrid cloud data architectures. Responsibilities include designing relational and dimensional data models, implementing Slowly Changing Dimensions (SCD), supporting ETL/ELT processes, and collaborating with data engineering and business intelligence teams. The role also requires partnering with application developers, data engineers, BI teams, and business stakeholders; mentoring junior developers; participating in code reviews; enforcing database standards; and troubleshooting production issues through root cause analysis. Requirements Minimum 8 years of experience as a Database Developer, Data Engineer, or in a similar role. Strong expertise in SQL Server and Azure SQL. Advanced proficiency in T-SQL, including query optimization and performance tuning. Hands-on experience with Databricks and Apache Spark. Experience with Delta Lake, Spark SQL, PySpark, and SQL-based data processing. Strong understanding of data warehousing, dimensional modeling, and Slowly Changing Dimensions. Experience designing and supporting ETL/ELT processes. Experience working in Azure cloud environments and hybrid data architectures. Knowledge of database security, data integrity, reliability, indexing, and performance optimization. Strong analytical, problem-solving, collaboration, communication, and leadership skills. Education and Certifications Degree in Engineering, Computer Science, or a related discipline, such as BE, ME, BTech, MTech, BSc, or MSc. Technical certifications across relevant technologies are desirable. Location and Work Arrangement Chicago, Illinois. Hybrid work arrangement requiring three days per week in the office. Candidates must be able to relocate to Chicago and work from the first day. The client interview may be conducted virtually. Read more

The organization is seeking a contract Data Engineer to design, develop, optimize, and maintain data pipelines, analytics solutions, and dashboards on cloud-based data platforms. The role will support program needs by leveraging Azure Synapse Analytics, Azure Data Factory, Power BI, and integrations with Salesforce and/or Curam/Oracle. Key Responsibilities Analyze source systems and develop scalable ETL/ELT pipelines using Azure Synapse, Azure Data Factory, and related Azure services. Build and manage Salesforce data ingestion workflows, including API integrations, schema alignment, and performance tuning. Develop and maintain data models, transformations, and semantic layers for Power BI reporting and analytics. Optimize Synapse pipelines, SQL queries, and data storage for performance, reliability, and cost efficiency. Troubleshoot pipeline failures, Salesforce API issues, and Power BI dataset or dataflow refresh problems. Requirements At least 5 years of hands-on experience configuring, designing, developing, and testing Power BI dashboards. At least 5 years of experience supporting Power BI datasets, dataflows, and DirectQuery/Import models. At least 3 years of experience working with structured and semi-structured data formats, including JSON, CSV, and Parquet. At least 3 years of experience designing and optimizing scalable data pipelines using platforms such as Azure Synapse, Snowflake, or Databricks. At least 5 years of advanced SQL experience, including query writing, ETL/ELT, performance tuning, and optimization. At least 3 years of proficiency in Python or Scala for data processing. At least 5 years of hands-on experience developing efficient PL/SQL procedures. At least 2 years of experience with SQL, T-SQL, programming, scripting, and data query optimization. At least 2 years of experience with Azure cloud services, including Synapse, Data Lake, Data Factory, Azure SQL, and monitoring tools. At least 2 years of experience with Azure Data Lake Storage, Delta Lake, data modeling, and data warehousing concepts such as star and snowflake schemas. Technology Environment Key technologies include Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, Delta Lake, Azure SQL, Power BI, Salesforce, Curam/Oracle, Snowflake, Databricks, SQL, T-SQL, PL/SQL, Python, and Scala. Read more

We are seeking a Senior Data Engineer to lead a greenfield and future-state data platform initiative within a regulated healthcare and medical scheme administration environment. The successful candidate will own delivery end to end, from discovery and assessment through to implementation. The role requires an autonomous technical lead who can work across complex legacy data environments while supporting the transition to modern cloud-based data platforms. The primary focus will be on reducing operational workload and improving business efficiency through: Reporting rationalisation and standardisation Process and data quality automation Self-service analytics enablement Development of reusable data assets Improved data governance, metadata and cataloguing Identification and delivery of measurable operational efficiencies Key responsibilities include: Assessing and documenting the current reporting and data landscape Identifying manual, repetitive and inefficient processes Quantifying workload and prioritising initiatives based on business value Reviewing, consolidating and standardising reporting assets Defining consistent data and metric definitions Designing and implementing robust ETL and data engineering solutions Automating validation, reconciliation, quality assurance and audit controls Developing reusable datasets and governed Power BI assets Establishing data catalogue and metadata standards Exploring Generative AI and LLM applications for data and report discovery Engaging with business and technical stakeholders to shape requirements and delivery plans Tracking KPIs related to reduced manual effort, released capacity and operational improvement Owning planning, prioritisation and delivery across assigned workstreams Requirements The ideal candidate will have strong hands-on experience in the following areas: Oracle Database Advanced SQL development and optimisation SAP BusinessObjects SAS Power BI and self-service analytics ETL and data engineering Data profiling, quality assessment and automation Data modelling Snowflake and AWS Metadata management and data cataloguing Generative AI and LLM applications The successful candidate should also: Be an experienced Senior Data Engineer with strong technical depth Be able to work independently with minimal supervision Have experience managing delivery from discovery through implementation Be comfortable working with complex, legacy or undocumented data environments Demonstrate strong data engineering, automation, data quality and governance skills Have the ability to quickly understand complex data estates and identify improvement opportunities Be commercially minded and focused on reducing operational effort Be confident engaging with senior business and technical stakeholders Be comfortable working with sensitive healthcare data in a regulated, POPIA-conscious environment Be outcome-focused, with the ability to measure delivery through efficiency gains and released capacity Contract and Location Position: Senior Data Engineer Contract: Up to 18 months, structured in six-month phases Start date: 1 October 2026 Work model: Hybrid Location: Waterfall, Midrand, Johannesburg Ideal Candidate Mindset This role is suited to a self-directed professional who can enter a complex environment, understand the current state, identify the highest-value opportunities, develop a delivery plan and execute against measurable outcomes. The successful candidate will focus not only on building data solutions, but also on using data engineering, automation and modern analytics to simplify the reporting estate, reduce manual work and create sustainable business capacity. Read more