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GCP Data Engineer designing, developing, and optimizing scalable cloud-based data pipelines using Google Cloud Platform, BigQuery, DBT, and Apache Airflow. The role requires 5+ years of experience in data engineering and expertise in building ELT/ETL pipelines.
Lead Data Analytics Engineer defining, building, and evolving the analytics data layer (warehouses, pipelines, data products) on GCP using BigQuery, Cloud Composer, Dataflow, and Python/SQL, while establishing engineering best practices and mentoring data engineers.
Senior Data Engineer building data reconciliation frameworks and ETL/ELT pipelines to ensure financial data integrity across multiple systems, primarily using SQL and data warehousing technologies.
Senior Data Engineer designing, building, and optimizing scalable ETL/ELT pipelines using PySpark, SQL, and Python, with a strong emphasis on Dataiku (DataIQ) integration and cross-functional stakeholder collaboration.
Senior Data Engineer in Mumbai designing and maintaining data pipelines, data marts, and data warehouse solutions on AWS and Snowflake to support BI and advanced analytics for internal stakeholders.
Lead a team of 8-10 data engineers while spending 30-50% of time hands-on building ETL/ELT pipelines using PySpark, SQL, and Azure cloud, working with enterprise data sources like SAP.
The Senior Data Engineer will design and optimize scalable data pipelines and cloud-based analytics solutions using the Azure ecosystem. The role involves collaborating in an Agile environment to build robust data integration, transformation, and reporting systems.
Senior Data Engineer designing, building, and maintaining scalable ETL/ELT data pipelines and data transformation workflows using DBT, Python, PySpark, SQL, and cloud platforms (GCP preferred).
Senior Data Engineer designing, developing, and maintaining scalable ETL/ELT data pipelines and cloud-based data integration solutions using AWS or Azure, SQL, and Python.
Senior Data Engineer working on-site in Bengaluru or Hyderabad, building ETL/ELT pipelines and data warehouses using AWS services (Glue, EMR, Redshift, S3, Athena) with Python, PySpark, and SQL.
Senior Data Analytics Engineer designing and maintaining the full analytics data layer—building scalable ETL pipelines, managing BigQuery warehouses, and creating visualizations using GCP (BigQuery, Cloud Composer, Dataflow, PubSub), Python, SQL, and Airflow.
Senior Data Engineer owning an Azure-based data platform—building ETL/ELT pipelines and a master data quality layer to produce trusted golden records from messy multi-system data.
Design, build, and optimize scalable Snowflake-based data solutions in the cloud, collaborating with analysts and scientists on ETL/ELT pipelines and modern data warehouse architecture.
Data engineer handling ETL processes, data warehousing, and provider credentialing operations using SQL, Python, and data visualization tools for a healthcare benefits company on a US night shift.
Senior Data Engineer building scalable ETL pipelines and data platforms using Apache Spark/PySpark on AWS services like Glue, S3, and Athena for Cloudwick's Amorphic Data Cloud.
Design and build end-to-end data engineering solutions on Microsoft Fabric (Lakehouse, Dataflows Gen2, Pipelines) and Azure (ADLS Gen2, ADF, Synapse) using PySpark and SQL, with CI/CD via Azure DevOps.
Senior Data Engineer designing and implementing scalable data warehouse and data engineering solutions, managing data schemas, SQL tuning, and code reviews using Azure, Snowflake, Kafka, DBT, and Python.
Data Engineer designing and maintaining scalable data integration pipelines using Informatica IDMC (CDI/CAI), with SQL, Python, and Unix/Linux scripting on cloud platforms like Oracle OCI, Databricks, or Azure in an offshore delivery model.
Data Engineer building and optimizing Snowflake-based data pipelines and ETL/ELT workflows for banking/financial services clients. Core tech: Snowflake, SQL, Python, and cloud platforms (AWS/Azure/GCP).
Designing, developing, and optimizing scalable data pipelines, data models, and analytics solutions using DBT, AWS, Snowflake, Redshift, and Tableau.
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