Verified Job
IT / Software / Data Analyst
Data Engineer (Databrick + Pyspark)
IT / Software / Data Analyst
#16481
Remote / WFH
Capco
Job Description
Job Title: Data Engineer (PySpark / Databricks)
Experience: 5–9 Years Location: Pune (Hybrid – Capco Office)
Job Summary
We are looking for a skilled Data Engineer with strong expertise in PySpark, Databricks, and modern data engineering practices. The ideal candidate will have hands-on experience in building scalable data pipelines, working with large datasets, and leveraging cloud-based data platforms.
Key Responsibilities Design, develop, and maintain scalable ETL/ELT data pipelines Work extensively with PySpark and Apache Spark for large-scale data processing Build and manage workflows using Apache Airflow Develop and optimize data solutions on Databricks (Jobs, Delta Lake) Work with cloud-based data lakes (S3 or equivalent) Write efficient and complex SQL queries for data transformation and analysis Run and manage Spark workloads on EMR Serverless or other managed Spark platforms Ensure data quality, reliability, and performance optimization of pipelines Must Have Skills Strong hands-on experience with PySpark and Apache Spark internals Experience with Databricks (Jobs, Delta Lake) Proficiency in Apache Airflow for workflow orchestration Solid experience building ETL/ELT pipelines at scale Strong SQL skills and experience with Data Warehouse (DWH) systems Experience running Spark workloads on EMR Serverless or managed Spark platforms Hands-on experience with cloud data lakes (S3 or equivalent) Good to Have Skills Experience with Delta Lake / Apache Iceberg Exposure to streaming frameworks (Spark Structured Streaming, Kafka) Familiarity with CI/CD pipelines for data engineering workflows Knowledge of data governance, cataloging, and lineage tools
Experience: 5–9 Years Location: Pune (Hybrid – Capco Office)
Job Summary
We are looking for a skilled Data Engineer with strong expertise in PySpark, Databricks, and modern data engineering practices. The ideal candidate will have hands-on experience in building scalable data pipelines, working with large datasets, and leveraging cloud-based data platforms.
Key Responsibilities Design, develop, and maintain scalable ETL/ELT data pipelines Work extensively with PySpark and Apache Spark for large-scale data processing Build and manage workflows using Apache Airflow Develop and optimize data solutions on Databricks (Jobs, Delta Lake) Work with cloud-based data lakes (S3 or equivalent) Write efficient and complex SQL queries for data transformation and analysis Run and manage Spark workloads on EMR Serverless or other managed Spark platforms Ensure data quality, reliability, and performance optimization of pipelines Must Have Skills Strong hands-on experience with PySpark and Apache Spark internals Experience with Databricks (Jobs, Delta Lake) Proficiency in Apache Airflow for workflow orchestration Solid experience building ETL/ELT pipelines at scale Strong SQL skills and experience with Data Warehouse (DWH) systems Experience running Spark workloads on EMR Serverless or managed Spark platforms Hands-on experience with cloud data lakes (S3 or equivalent) Good to Have Skills Experience with Delta Lake / Apache Iceberg Exposure to streaming frameworks (Spark Structured Streaming, Kafka) Familiarity with CI/CD pipelines for data engineering workflows Knowledge of data governance, cataloging, and lineage tools
