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Tier-1 brand, metro location, common data engineering skills, and broad role requirements increase competition.
Core Databricks/Python/Spark skills are transferable, but securities domain preference raises sensitivity to medium.
Mandatory Databricks, Python, Spark, and cloud skills create strict technical filters, so high.
Design, build, and optimize scalable data pipelines and transformation workflows on Databricks using Python and Spark.
Collaborate with Data Architects and Business Analysts to develop business-aligned, robust data models and deliver compliant data solutions.
Implement and validate data quality checks and maintain documentation of ETL logic, datasets, and pipeline metadata following governance standards.
Proven experience developing data pipelines and solutions on Databricks using Python and Spark.
Proficiency in Python for data transformation including libraries such as pandas.
Experience with Spark and cloud data platforms.
Work Experience Required: Not explicitly mentioned in the JD.
Experience working in financial services or large enterprise data environments with awareness of data governance and compliance.
Ability to collaborate cross-functionally with Data Architects and Business Analysts to translate business needs into technical data models.
Detail-oriented with the capability to document data flows and transformation logic clearly and maintain project tracking with tools like Jira.