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Tier-1 bank, Pune metro and a popular mid-level cloud data role drive high candidate competition.
Core cloud data engineering skills transfer well, though banking controls and Snowflake experience increase domain specificity.
Mandatory Snowflake, PySpark, AWS, DBT skills and banking risk controls make shortlisting highly selective.
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Build and maintain data architectures and pipelines handling durable, complete, and consistent data transfer and processing.
Design and implement scalable data warehouses and lakes ensuring appropriate volume handling and security compliance.
Collaborate with data scientists to develop and deploy machine learning models and develop processing algorithms for complex data volumes.
Hands-on experience with PySpark, DataFrames, RDD, and SparkSQL.
Experience developing, testing, and maintaining applications on AWS Cloud including AWS Data Analytics technologies: Glue, S3, Lambda, Lake Formation, Athena.
Proficiency in Snowflake for data transformation and storage; experience with data ingestion using formats like Parquet, Iceberg, JSON, CSV.
Work Experience Required: At least involvement in two major project implementations; Location: Pune based.
Experienced in designing and implementing cloud-based enterprise data warehouses using Snowflake and NoSQL environments.
Familiar with orchestration tools such as Apache Airflow or Snowflake Tasks and data governance tools like Immuta or Alation (preferred).
Capable of engaging with stakeholders to translate requirements into ETL components and providing solutions related to infrastructure setup.