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Azure Data Engineer with around 3 years of experience designing, developing, and supporting scalable cloud-based data solutions across healthcare and business environments. I build end-to-end ETL/ELT pipelines on Azure using Data Factory, Databricks, Synapse, and storage services, and I transform structured and semi-structured data into reliable analytics-ready datasets. I’m hands-on with Python, SQL/T-SQL, PySpark/Spark SQL, and Delta Lake/Medallion architecture. I focus on incremental/batch loading, data quality and reconciliation, secure governance (Key Vault, RBAC, Managed Identities, Unity Catalog), and production monitoring/troubleshooting—so teams can trust the data powering dashboards and decisions.…Azure Data Engineer with around 3 years of experience designing, developing, and supporting scalable cloud-based data solutions across healthcare and business environments. I build end-to-end ETL/ELT pipelines on Azure using Data Factory, Databricks, Synapse, and storage services, and I transform structured and semi-structured data into reliable analytics-ready datasets. I’m hands-on with Python, SQL/T-SQL, PySpark/Spark SQL, and Delta Lake/Medallion architecture. I focus on incremental/batch loading, data quality and reconciliation, secure governance (Key Vault, RBAC, Managed Identities, Unity Catalog), and production monitoring/troubleshooting—so teams can trust the data powering dashboards and decisions.

Sayyed Mansoor Ahmed

Data Engineer, Software Engineer, Cloud Developer, +2

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Azure Data Engineer with around 3 years of experience designing, developing, and supporting scalable cloud-based data solutions across healthcare and business environments. I build end-to-end ETL/ELT pipelines on Azure using Data Factory, Databricks, Synapse, and storage services, and I transform structured and semi-structured data into reliable analytics-ready datasets. I’m hands-on with Python, SQL/T-SQL, PySpark/Spark SQL, and Delta Lake/Medallion architecture. I focus on incremental/batch loading, data quality and reconciliation, secure governance (Key Vault, RBAC, Managed Identities, Unity Catalog), and production monitoring/troubleshooting—so teams can trust the data powering dashboards and decisions.…Azure Data Engineer with around 3 years of experience designing, developing, and supporting scalable cloud-based data solutions across healthcare and business environments. I build end-to-end ETL/ELT pipelines on Azure using Data Factory, Databricks, Synapse, and storage services, and I transform structured and semi-structured data into reliable analytics-ready datasets. I’m hands-on with Python, SQL/T-SQL, PySpark/Spark SQL, and Delta Lake/Medallion architecture. I focus on incremental/batch loading, data quality and reconciliation, secure governance (Key Vault, RBAC, Managed Identities, Unity Catalog), and production monitoring/troubleshooting—so teams can trust the data powering dashboards and decisions.

Available to hire

Azure Data Engineer with around 3 years of experience designing, developing, and supporting scalable cloud-based data solutions across healthcare and business environments. I build end-to-end ETL/ELT pipelines on Azure using Data Factory, Databricks, Synapse, and storage services, and I transform structured and semi-structured data into reliable analytics-ready datasets.

I’m hands-on with Python, SQL/T-SQL, PySpark/Spark SQL, and Delta Lake/Medallion architecture. I focus on incremental/batch loading, data quality and reconciliation, secure governance (Key Vault, RBAC, Managed Identities, Unity Catalog), and production monitoring/troubleshooting—so teams can trust the data powering dashboards and decisions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Beginner

Beginner

Work Experience

Azure Data Engineer at Bill

January 1, 2025 - Present

Designed, developed, and maintained scalable ETL/ELT pipelines using Azure Data Factory, Azure Databricks, ADLS Gen2, Azure Synapse Analytics, PySpark, SQL, and Python to ingest, transform, and deliver analytics-ready datasets from enterprise sources. Built reusable, parameterized, metadata-driven ADF pipelines (Linked Services, Datasets, Triggers, Lookup, For Each, Copy Activity, variables, and conditional workflows) to reduce repetitive development by ~20%. Implemented batch and incremental loading to efficiently process new/modified records, improving execution time by ~15%. Developed a Lakehouse architecture with ADLS Gen2, Delta Lake, and Medallion layers (bronze/silver/gold) and created Databricks notebooks for cleansing, schema validation, joins, aggregations, deduplication, and business-rule transformations. Optimized Spark workloads via partitioning/caching/joins to reduce processing time by ~20%. Delivered dimensional modeling with Star Schema, fact/dimension tables, surrogat

Data Engineer at Graphene Med Resources LLP

May 1, 2023 - December 31, 2023

Developed and maintained data pipelines integrating healthcare product, customer, quality, and operational data from SQL databases, flat files, REST APIs, and cloud storage. Automated ingestion and transformation workflows using Azure Data Factory; used Azure Databricks with PySpark/Spark SQL and Python for cleansing, transformation, joins, aggregations, and validation. Organized datasets using Delta Lake and Medallion architecture to improve consistency and accessibility. Performed profiling, schema validation, null handling, duplicate detection, and source-to-target reconciliation. Wrote SQL queries/views/stored procedures to support healthcare operations and reporting, and implemented incremental loading to capture new/modified records while reducing full refreshes. Monitored pipeline runs, reviewed logs, resolved ingestion/transformation/schema issues, and maintained source-to-target mappings and transformation documentation for operational support.

Data Engineer Intern at Graphene Med Resources LLP

November 1, 2022 - April 30, 2023

Assisted in collecting and organizing healthcare-related data from databases and flat files, supporting data cleansing by handling missing values, duplicates, formatting issues, and inconsistent fields. Wrote basic SQL joins/filters/views to prepare datasets for reporting and analysis. Helped validate processed outputs by comparing source records to transformed results and supported creation of source-to-target mappings and transformation rules. Monitored scheduled processing activities, reviewed error logs, documented validation/loading issues, and supported troubleshooting of schema mismatches and data-quality problems. Maintained technical documentation and validation reports while following healthcare data privacy/confidentiality standards.