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Build and optimize reliable, scalable data pipelines using Python, SQL, PySpark, and Azure tools to feed analytics and AI models for enterprise clients.
Build and maintain ETL/ELT pipelines connecting NetSuite, Oracle, and other sources to an AWS data lake/warehouse, then create Power BI and Tableau dashboards for healthcare analytics.
Senior Data Engineer builds and scales data pipelines on Databricks and AWS, designing ETL/ELT workflows for large datasets using Python and SQL.
Build and maintain AWS-based data pipelines and ETL processes for a global financial data provider, using Python, Spark, and modern cloud tools to enable AI-ready analytics.
Build and maintain cloud-based data pipelines and warehouses using SQL, Python, Snowflake, and AWS to power analytics and reporting for clients.
Designs and optimizes data architectures for a global tech firm, transitioning legacy systems into scalable, high-performance data ecosystems using SQL, Python, and cloud warehousing.
Design and maintain ETL workflows using SAP BODS, build scalable data pipelines, and optimize SQL/Teradata queries for data transformation and migration.
Build and maintain secure, scalable data pipelines and ETL workflows using Airflow, Snowflake, and DBT to support healthcare analytics and research insights.
Builds and maintains data pipelines and ingestion frameworks in a data lake, using Databricks/Spark and SQL to support Power BI reporting and ensure regulatory compliance.
Designs and builds Azure-based data pipelines and lakehouse solutions using ETL/ELT workflows and SQL.
Build and maintain data pipelines, cloud data warehouses, and RESTful APIs using Python, GCP, and FastAPI/Flask to support scalable data-driven applications.
Design and optimize Azure-based data pipelines using PySpark, SQL, and Databricks, and warehouse data in Snowflake while enforcing governance standards.
Designs and maintains scalable ETL/ELT pipelines for manufacturing data to support analytics, reporting, and AI/ML initiatives.
Builds and maintains data pipelines and ETL workflows in a data lake, using Databricks, Spark, and SQL to ingest and transform structured, semi-structured, and unstructured data for reporting.
Designs and builds scalable data pipelines, optimizes Snowflake schemas, and enforces DataOps with CI/CD, Docker, and automated testing in Python.
Design and maintain scalable data pipelines and cloud architectures, transforming raw data into insights for strategic decisions.
Senior Data Engineer builds and scales a modern data platform, designing ETL/ELT pipelines, optimizing Snowflake schemas, and implementing DataOps with Airflow/Prefer/Dagster.
Designs, builds, and maintains scalable data pipelines and warehouses using SQL, Spark, Databricks, and Snowflake to ensure clean, reliable data for analytics and decision-making.
Designs and builds scalable data pipelines on Google Cloud Platform (BigQuery, Data Fusion, Airflow) to support HR analytics and business decision-making.
Build and maintain secure, scalable data pipelines and infrastructure using Airflow, Snowflake, and DBT to support analytics and healthcare research globally.
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