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Dynamic Data Engineer with hands-on experience designing and implementing scalable big data solutions using Apache Spark and MapReduce. Proficient in Python, Scala, and Java, with strong experience building cloud-native data platforms on AWS using services such as S3, AWS Glue, EMR, Lambda, Redshift, Athena, and Kinesis. Proven ability to process large-scale structured and semi-structured datasets, optimize ETL and ELT workflows, and design high-performance OLAP and OLTP systems. Experienced in applying solid data modeling techniques, including dimensional modeling, star schemas, and slowly changing dimensions, to support analytics and reporting. Strong focus on data quality, validation, and governance, implementing checks for completeness, consistency, and accuracy across pipelines. Well-versed in delivering data solutions across healthcare, finance, and telecom domains, with strong problem-solving and stakeholder communication skills to translate complex data architectures into actionable insights.…Dynamic Data Engineer with hands-on experience designing and implementing scalable big data solutions using Apache Spark and MapReduce. Proficient in Python, Scala, and Java, with strong experience building cloud-native data platforms on AWS using services such as S3, AWS Glue, EMR, Lambda, Redshift, Athena, and Kinesis. Proven ability to process large-scale structured and semi-structured datasets, optimize ETL and ELT workflows, and design high-performance OLAP and OLTP systems. Experienced in applying solid data modeling techniques, including dimensional modeling, star schemas, and slowly changing dimensions, to support analytics and reporting. Strong focus on data quality, validation, and governance, implementing checks for completeness, consistency, and accuracy across pipelines. Well-versed in delivering data solutions across healthcare, finance, and telecom domains, with strong problem-solving and stakeholder communication skills to translate complex data architectures into actionable insights.

Vindhya Reddy

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Dynamic Data Engineer with hands-on experience designing and implementing scalable big data solutions using Apache Spark and MapReduce. Proficient in Python, Scala, and Java, with strong experience building cloud-native data platforms on AWS using services such as S3, AWS Glue, EMR, Lambda, Redshift, Athena, and Kinesis. Proven ability to process large-scale structured and semi-structured datasets, optimize ETL and ELT workflows, and design high-performance OLAP and OLTP systems. Experienced in applying solid data modeling techniques, including dimensional modeling, star schemas, and slowly changing dimensions, to support analytics and reporting. Strong focus on data quality, validation, and governance, implementing checks for completeness, consistency, and accuracy across pipelines. Well-versed in delivering data solutions across healthcare, finance, and telecom domains, with strong problem-solving and stakeholder communication skills to translate complex data architectures into actionable insights.…Dynamic Data Engineer with hands-on experience designing and implementing scalable big data solutions using Apache Spark and MapReduce. Proficient in Python, Scala, and Java, with strong experience building cloud-native data platforms on AWS using services such as S3, AWS Glue, EMR, Lambda, Redshift, Athena, and Kinesis. Proven ability to process large-scale structured and semi-structured datasets, optimize ETL and ELT workflows, and design high-performance OLAP and OLTP systems. Experienced in applying solid data modeling techniques, including dimensional modeling, star schemas, and slowly changing dimensions, to support analytics and reporting. Strong focus on data quality, validation, and governance, implementing checks for completeness, consistency, and accuracy across pipelines. Well-versed in delivering data solutions across healthcare, finance, and telecom domains, with strong problem-solving and stakeholder communication skills to translate complex data architectures into actionable insights.

Available to hire

Dynamic Data Engineer with hands-on experience designing and implementing scalable big data solutions using Apache Spark and MapReduce. Proficient in Python, Scala, and Java, with strong experience building cloud-native data platforms on AWS using services such as S3, AWS Glue, EMR, Lambda, Redshift, Athena, and Kinesis. Proven ability to process large-scale structured and semi-structured datasets, optimize ETL and ELT workflows, and design high-performance OLAP and OLTP systems. Experienced in applying solid data modeling techniques, including dimensional modeling, star schemas, and slowly changing dimensions, to support analytics and reporting. Strong focus on data quality, validation, and governance, implementing checks for completeness, consistency, and accuracy across pipelines. Well-versed in delivering data solutions across healthcare, finance, and telecom domains, with strong problem-solving and stakeholder communication skills to translate complex data architectures into actionable insights.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Work Experience

Data Engineer at AstraZeneca

October 1, 2023 - Present

Optimized PostgreSQL through SQL query refactoring, tuning by reducing the query retrieval time from 90 secs to 20 secs, reducing table scans for over 20 million records. Managed Fivetran pipelines to automate integration of 10+ data sources, reducing manual data handling by 40%. Orchestrated ETL/ELT jobs: daily, weekly, and monthly to process data from disparate data sources from S3 to data warehouse using various sensors and operators in Airflow.

Technology Consulting Analyst- Data at Accenture Ltd

May 1, 2022 - August 1, 2023

Built audit trail and data lineage reports using dbt artifacts + Snowflake metadata for regulatory inspections, improving data traceability coverage by 100%. Streamlined CI/CD pipelines using Github for version controlling and Jenkins while following DevOps best practices.

Associate Data Engineer at Virtusa Consulting Services

June 1, 2018 - December 1, 2019

Designed and implemented a scalable Hadoop-based data pipeline to process massive volumes of telecom billing and transactional data, improving data processing efficiency by 45%. Utilized Apache Nifi data ingestion pipelines to efficiently ingest 50+ tables into Hive, ensuring seamless data integration and transformation.