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Lead the design and optimization of scalable Azure data pipelines using Databricks, PySpark, and ADF, while mentoring engineers and collaborating with cross-functional teams.
Senior to Lead Data Engineer builds and optimizes IBM Cognos reports, dashboards, and data models for business intelligence, using SQL and Oracle databases.
Leads a team building and optimizing scalable data pipelines on Azure Databricks and Microsoft Fabric to power BI and AI use cases across enterprise platforms.
Lead a team that builds and maintains scalable data pipelines and warehouses for a Philippine bank, using Python, SQL, Snowflake, DBT, and Airflow to ensure clean, reliable data for analytics and decision-making.
Lead a team to build and optimize scalable data pipelines using Snowflake, Databricks, and Kafka, ensuring security, governance, and performance for a global fast-food company.
Lead a team of data engineers to design, build, and optimize cloud-based data pipelines and warehouses using Python, SQL, Spark, and cloud platforms like Azure or AWS.
Lead a team building and maintaining scalable data pipelines for analytics using ETL/ELT tools, Airflow, DBT, and Snowflake/Redshift.
Lead a data engineering team to design and scale modern data pipelines for a growing fintech company, ensuring data quality and alignment across stakeholders.
Lead a team to design and build data pipelines and transformations using Azure and Databricks, turning raw data into insights for asset management.
Leads cloud-based data pipelines and analytics for media performance reporting using SQL, Python, and Databricks to ensure data quality and governance.
Lead a team to design and build scalable data pipelines using Azure Databricks, ADF, and PySpark, while integrating with AWS, Snowflake, and BigQuery in hybrid/multi-cloud environments.
Lead the end-to-end data architecture—ingestion, processing, modeling, and consumption—using Python, PySpark, Airflow, and AWS services to enable reliable reporting and LLM-driven analytics at scale.
Lead data pipelines and ensure high data quality using Databricks, Python, ETL tools, and cloud platforms while collaborating with teams on architectural decisions.
Lead the build-out of AI-driven data infrastructure on Azure/Databricks, ensuring reliable pipelines for analytics and ML workloads using Spark/Scala.
Leads design and delivery of cloud-based data platforms using AWS services like Redshift, Glue, and PySpark, ensuring scalable, secure data solutions for analytics and governance.
Lead the design and delivery of a scalable enterprise data platform, building ETL/ELT pipelines and enabling analytics and AI across cloud and hybrid environments.
Design and operate cloud-based data pipelines to collect, clean, and transform raw data for business insights in a hybrid fintech setting.
Lead a distributed team of data engineers, design cloud-scale data architectures, and mentor engineers while staying ahead of data/AI trends for high-impact client projects.
Lead a team to design, build, and maintain data pipelines and systems that transform raw healthcare data into actionable insights for analysts and business teams using Python, SQL, Databricks, and Azure.
Leads a team building a petabyte-scale data platform for aerospace operations, simulations, and ground systems using Python and software engineering best practices.
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