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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.
Build and maintain scalable data pipelines using Spark, Scala, Airflow, and Azure Databricks in a hybrid role based in Bengaluru. Work with modern data lakehouse technologies, containerization, and CI/CD practices.
Senior Data Engineer / AI Data Platform Engineer building data pipelines and AI platforms using Python, Spark, Airflow, Databricks on AWS, and GenAI/LLM/RAG technologies.
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.
Senior Data Engineer designing, building, and operating data pipelines and a lakehouse platform on Databricks and Microsoft Fabric using Spark, Python, and SQL.
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).
Data Engineer designing and managing ETL pipelines and data infrastructure for a consumer tech company focused on short-form vertical content. Core tech: SQL, Python, Airflow, dbt, cloud data platforms (AWS/GCP), data warehouses, and streaming tools.
Build and maintain an enterprise data lake on BigQuery, design ETL pipelines in Python across ERP/CRM sources, and develop ML forecasting models and AI agents using LLM APIs.
Data Engineer owning ELT/ETL pipelines, data models, and quality controls for cloud data platforms, with secondary responsibility for production ML pipelines powering a shopping cart computer-vision classifier. Core tech: SQL, Python, Azure/GCP, Airflow/Prefect, Spark/Databricks.
Data Engineer designing, developing, and maintaining scalable ETL/ELT pipelines, data warehouses, and data lakes using SQL, Python, and Big Data technologies (Spark, Databricks) on Azure/cloud platforms for an Azure-focused managed services company.
Design, develop, and optimize large-scale data processing solutions and high-performance data pipelines using Spark, Scala, and the Hadoop ecosystem for distributed analytics platforms.
Big Data Engineer designing, developing, and optimizing scalable data pipelines using PySpark, Hadoop ecosystem tools (HDFS, Hive, Sqoop), SQL/HiveQL, and workflow orchestration via Airflow or Oozie.
Designs, develops, and manages cloud-based data integration pipelines using Fivetran. Works with SQL, cloud data warehouses (Snowflake, Databricks, BigQuery, Redshift, Azure Synapse), and dbt to deliver reliable data for reporting and analytics.
Lead Data Engineer designing and building scalable batch and real-time data pipelines using Scala, Apache Spark, SQL, Kafka, and cloud platforms (AWS/Azure/GCP).
Mid-Level Big Data Engineer with 4-6 years of experience building and supporting large-scale Big Data applications and cloud-based data pipelines using Python, AWS EMR, Spark, SQL, and AWS cloud services with focus on EMR performance tuning and cost optimization.
Hands-on Data Engineer II building and maintaining scalable data pipelines on GCP, working with BigQuery, SQL, Python, Dataform/dbt, Cloud Composer/Airflow, and Dataflow/Apache Beam in a hybrid role based in Gurgaon.
Platform Engineer configuring and optimizing GCP services (Dataproc, DataFlow, Composer/Airflow, PubSub, GCS) using Terraform and Python scripting.
Principal Data Engineer building and optimizing big data pipelines and infrastructure for a US healthtech company delivering integrated at-home and virtual care, based in Bangalore.
Build and maintain scalable ETL/ELT data pipelines and optimize data infrastructure using Python, SQL, and big data technologies like Spark, Kafka, and cloud data warehouses.
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