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GCP Data Engineer on an EST hybrid shift in Noida, designing data warehouse solutions, building ETL/ELT pipelines, and developing BI reporting for a US-based media client.
Design, build, and maintain the analytics data layer—pipelines (Airflow), warehouse (BigQuery), and ETL—on GCP, applying software engineering best practices to deliver BI solutions.
Lead Data Engineer building end-to-end data platforms using Medallion architecture, dbt, Python, and cloud services (AWS/GCP/Azure) for client engagements, with hands-on coding, architectural decisions, and mentoring responsibilities.
Hands-on Technical Lead / Senior Data Engineer leading an offshore BAU Data Engineering team, maintaining and improving GCP data pipelines with a focus on BigQuery, Cloud Composer/Airflow, Python, and SQL production support.
Lead Data Engineer architecting cloud-native data platforms (data lakes, lakehouses, warehouses) for PE portfolio companies, using tools like Databricks, Snowflake, Azure Synapse, dbt, and AI tooling to build AI-ready analytics infrastructure.
Senior Data Engineer designing and building cloud-native data platforms (Snowflake, Databricks, BigQuery, etc.) with ELT/ETL pipelines, CI/CD, and AI-ready infrastructure for a financial consulting firm serving private equity portfolio companies.
Design, develop, and optimize big data ETL pipelines using Apache Spark and Databricks on Azure cloud, while collaborating with analysts and implementing CI/CD and security best practices.
Lead GCP Data Engineer designing and deploying end-to-end data lake and analytics solutions on Google Cloud Platform for industrial and government sector clients, including pre-sales and proposal/bid work.
Data Engineer building scalable data ingestion and integration pipelines on Adobe Experience Platform (AEP) and Google Cloud Platform (GCP), collaborating with architects to deliver production-ready data solutions for enterprise customer data ecosystems.
Senior Data Engineer building secure, automated, scalable GCP data pipelines using Python, Apache Airflow, Apache Druid, and Spark for a global ad-tech DSP platform.
Data Engineer designing and maintaining scalable data pipelines using dbt Cloud, Apache Airflow, and GCP BigQuery for a Big 4 firm in the Financial Services domain.
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 scalable GCP data pipelines end-to-end—from design through production support—using BigQuery, Python, SQL, Cloud Composer/Airflow, Dataflow/Apache Beam, and Dataform/dbt.
Build and optimize scalable data pipelines and ETL/ELT workflows for large datasets using Python and SQL on GCP/AWS, focusing on identity resolution and ID graph 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 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 building and operating production-grade data pipelines on AWS (S3, Glue, EMR, Redshift, Lambda) using Python and SQL, with Airflow, Delta Lake, and streaming tools, for a political/policy research analytics firm in Bangalore (hybrid).
Senior Data Engineer designing and building scalable, cloud-native data pipelines and platforms using Python, Apache Airflow/Google Cloud Composer, and GCP to power analytics, reporting, and ML.
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