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Tier-1 brand, generic Data Engineer title, metro location, and broad skillset requirements increase applicant competition.
Core data engineering skills are transferable across industries, though asset-management domain knowledge is preferred.
Several mandatory technical skills (Snowflake/AWS, Python, SQL, Airflow) but no explicit years requirement.
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Take ownership and deliver components of data pipelines and applications within a broader data platform.
Develop, execute, and monitor data quality validation processes and write efficient SQL/Python scripts for data processing.
Participate in code reviews, maintain documentation, and troubleshoot data pipeline issues.
Proficiency in Python and SQL for data processing tasks.
Experience with cloud-based data platforms (Snowflake or equivalent) and AWS services (S3, Glue).
Familiarity with RDBMS systems like Oracle, Postgres, or MSSQL.
Work Experience Required: Not explicitly mentioned in the JD.
Senior data engineer capable of independent ownership and delivering subsections of data platforms or applications.
Experience working with cloud data ecosystems and modern data engineering tools like Airflow or Control-M.
Interest or willingness to learn investment management industry and asset management data domains.