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Tier-1 brand, metro location, common mid-level data skillset increases competition.
Core data engineering skills are transferable, though financial services experience moderately biases fit.
Mandatory 7-9 years and specific Databricks, Spark, Python skills enforce strict screening.
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Design and develop scalable batch ETL pipelines using Python and Apache Spark on Databricks (AWS).
Build and optimize data models and SQL transformations to support analytics and reporting platforms.
Maintain data quality, performance, and reliability in cloud-based data engineering environments.
7-9 years of experience in data engineering.
Strong expertise in Python, Apache Spark, Databricks on AWS, and SQL.
Experience with data warehousing and data modeling concepts.
Experience in large enterprise environments; financial services experience preferred.
Experienced in building and maintaining cloud-based big data pipelines using Python and Spark in AWS environments.
Skilled at developing performant and reliable data solutions at scale to support downstream analytics.
Comfortable working within large enterprise teams, particularly in financial services or similar regulated industries.