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Lead the design and modernization of enterprise data platforms using Informatica IDMC and Databricks Lakehouse, guiding large-scale data transformations for regulated industries.
Builds and optimizes AWS-based data pipelines and lake architectures using PySpark, SQL, and Delta Lake to enable reliable, data-driven decisions.
Build and maintain cloud data pipelines in Snowflake, transforming raw data into analytics-ready datasets for analysts and scientists across Medtronic’s healthcare products.
Designs scalable data pipelines and migrates analytics workloads from Redshift to a Databricks Lakehouse on AWS using PySpark and Spark.
Build and maintain scalable data pipelines and the Elastic Hierarchy framework using Python, AWS, Snowflake, and DBT to support analytics and ML in a hybrid SaaS/on-premise environment.
Designs and builds scalable cloud data pipelines and lake architectures using Python, PySpark, SQL, and AWS tools like Glue, Athena, and Redshift.
Data Engineer to migrate from Amazon Redshift to Databricks, building pipelines with AWS services like S3, Glue, and Athena while enforcing data governance.
Builds and maintains Databricks pipelines and jobs to migrate a data platform from Amazon Redshift to Databricks, using AWS services like S3, Glue, and Athena.
Senior Data Engineer to design, build, and optimize data pipelines and warehouses, migrating 1,000 pipelines to Snowflake using Talend, Active Batch, Docker, and GitHub.
Build and maintain Databricks pipelines and AWS data lake components during a Redshift-to-Databricks migration, focusing on data governance and RBAC.
Build and maintain ETL/ELT pipelines using Python, SQL, and AWS services (S3, Glue, Athena, Redshift) to process and integrate financial data for a cloud-ecosystem project.
Build and maintain Databricks pipelines and jobs to migrate a data platform from Amazon Redshift to Databricks, using AWS S3, Glue, and Athena.
Migrate data from Amazon Redshift to Databricks, build ETL pipelines using AWS Glue and Athena, and implement data governance for a modern data lake.
Design and maintain AWS-based data pipelines for a U.S. healthcare client, ensuring HIPAA/HITRUST compliance while ingesting and transforming clinical data with tools like S3, Glue, Redshift, and Airflow.
Build and scale data pipelines, warehouses, and analytics for a global fintech/crypto platform using Python, Spark, Kafka, and cloud tools.
Design and build scalable data pipelines and warehouses using Spark, Kafka, and Snowflake to power analytics and ML, enabling data-driven decisions in a remote-first team.
Builds and maintains data pipelines for digital health applications, processing multimodal biosensor time-series data (accelerometer, ECG, PPG, EEG) using Python, cloud-native tools, and AWS services.
Build and maintain cloud-based data pipelines on Snowflake and AWS, transforming raw data into analytics-ready datasets for cross-functional teams in a healthcare company.
Design, build, and optimize ETL pipelines and data warehouses using Python, PySpark, Databricks, and cloud platforms to power marketing analytics and digital media reporting.
Design and build Prospera AI’s data infrastructure from scratch, including Snowflake warehouse, ETL pipelines with dbt/Airflow, and ML feature stores to power analytics and AI model training.
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