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Tier-1 brand, popular Data Engineer title, metro location, and broad required skills drive high competition.
Core data engineering skills are transferable across industries despite banking controls.
Mandatory PySpark, Snowflake, AWS, DBT, and SQL skills enforce strict technical screening.
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Build and maintain data pipelines, data warehouses, and data lakes ensuring data accuracy, accessibility, and security.
Design and implement scalable and efficient data transformation and storage solutions using PySpark, AWS Data Analytics stack, and Snowflake.
Collaborate with data scientists to build and deploy machine learning models and support enterprise data warehouse initiatives on cloud platforms.
Hands-on experience with PySpark including Dataframes, RDD, and SparkSQL.
Proven experience with AWS data analytics technologies: Glue, S3, Lambda, Lake Formation, Athena.
Strong knowledge of Snowflake for data storage and ELT pipeline development using DBT.
Work Experience Required: Minimum of two major project implementations; Location Requirement: Pune-based role.
Experienced in developing, testing, and maintaining cloud-based data applications using AWS and Snowflake.
Familiarity with orchestration tools like Apache Airflow or Snowflake Tasks; experience with data governance tools such as Immuta or Alation is a plus.
Capable of engaging stakeholders to translate requirements into ETL components and provide infrastructure-related solutions.