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Builds and tests PySpark transformations on AWS Glue/S3, contributes to shared platform libraries, and follows CI/CD and IaC standards using GitLab and Terraform.
Build cloud-based data platforms and tools for biopharmaceutical R&D, using Python, JavaScript/TypeScript, React, AWS, and data stacks like Pandas and Airflow to accelerate drug development.
Senior Data Engineer builds and operates enterprise-scale data pipelines on AWS Lakehouse, implementing ELT/ETL, streaming ingestion, and DataOps practices to deliver trusted, analytics-ready datasets for healthcare operations.
Lead the technical evolution of a large-scale enterprise platform, defining architecture standards and guiding distributed teams on AWS, PostgreSQL, Snowflake, and ETL pipelines.
Build and lead CBA’s next-gen digital wealth platform using .NET, ASP.NET Core, React, and Next.js, designing scalable APIs and event-driven systems for mass affluent and high-net-worth customers.
Build and maintain ETL/ELT pipelines for financial data using Apache Spark and AWS Glue, ensuring data quality and traceability.
Mid-level software engineer building data pipelines and services in Python, PySpark, and AWS for a government-focused mission.
Lead Benevity’s Data Governance program: set standards, classify assets, enforce quality SLAs, and maintain the DataHub catalog so teams can trust their data.
Build and lead large-scale .NET full-stack systems for CBA’s wealth platforms, using ASP.NET Core, React, AWS, and event-driven architectures to power high-volume customer journeys.
Build and maintain data pipelines, optimize databases, and ensure data quality using SQL, Python, and AWS services like Redshift and S3.
Build and maintain AWS-based data pipelines and Redshift warehouses, writing Python/SQL and automating with GitLab CI/CD and Terraform.
Senior Data Engineer builds and maintains cloud cost visibility pipelines using Python, SQL, dbt, Airflow, AWS Glue, Athena, Aurora, and Snowflake to power cost optimization insights.
Designs and builds AWS-based ETL pipelines using Python, PySpark, Glue, and Kafka to move and transform data in Redshift, with CI/CD and Git workflows.
Build and optimize scalable ETL/ELT pipelines for a wealth-tech platform using Snowflake, AWS, and Python, ensuring data quality and governance in a financial-services environment.
Design and maintain AWS-based data pipelines and lakehouse architecture for environmental services, processing large datasets to support analytics and business intelligence.
Design and scale data pipelines for enterprise AI systems and analytics workloads using SQL, ETL/ELT, and cloud data platforms.
Designs and builds scalable cloud data pipelines on GCP and AWS, integrating batch and real-time streams into data warehouses and lakes while collaborating with AI teams on GenAI and agentic systems.
Design and maintain scalable AWS data pipelines using PySpark, SQL, and Terraform to build and optimize data lakes and lakehouse architectures.
Build and maintain scalable PySpark data pipelines on AWS using Glue, Lambda, and Step Functions, with Terraform for IaC and CI/CD for deployment.
Designs and maintains AWS-based data pipelines for SAP integration and ETL workflows using AWS Glue, ensuring data quality with DataOps practices.
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