Open to opportunities

Rajesh M

@rajeshm2

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Data engineer specializing in cloud-native ETL, big data pipelines, and scalable analytics solutions.

United States

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What I'm looking for

I seek a role developing scalable, cloud-native data pipelines where I can leverage AWS/Azure, Spark, and Snowflake to deliver reliable analytics and drive data-driven decisions.

I am a Data Engineer with four years of hands-on experience building scalable data pipelines and cloud-based data architectures using AWS and Azure. I design and implement ETL processes, orchestration, and data lakes to deliver reliable, high-performance analytics platforms.

I've implemented production solutions using AWS services (Glue, Lambda, EMR, Redshift, S3), Azure services (Data Factory, Databricks, Synapse), and orchestration tools like Airflow and Control-M. I develop Spark and PySpark jobs, automate deployments with CI/CD pipelines, and optimize performance and costs through right-sizing and data partitioning.

I combine strong programming skills in Scala, Python, SQL, and Java with experience in Snowflake, Hadoop ecosystems, NoSQL databases, and BI tools like Tableau and Power BI to translate complex data into actionable business insights.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Biogen

May 2024 - Present (1 year 10 months)

Designed and implemented AWS-based ETL and data lake architectures, migrating terabytes of data to Snowflake and Redshift while automating data quality checks and CI/CD pipelines to improve ingestion reliability and reduce manual deployment effort.

AWS Glue Pyspark Redshift Snowflake AWS Lambda CloudFormation EMR Docker CI CD

Data Engineer

HSBC

Jan 2021 - Jun 2023 (2 years 5 months)

Built end-to-end Azure data solutions using ADF, Databricks, and ADLS, optimized Spark jobs and SQL queries to reduce processing time by ~25%, and deployed automated workflows and containerized services to support scalable analytics.