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Tier-1 brand, mid-level, metro location, popular data role, and broad skillset increase competition.
Core data engineering skills are highly transferable across industries; finance domain knowledge is optional.
Mandatory cloud, Snowflake, Python, SQL and ETL experience raise screening rigor, but no explicit years required.
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Own and deliver components of data pipelines for ingestion, transformation, and data quality validation within the wider AMP Data Engineering platform.
Implement technical solutions based on specifications, including SQL queries and Python scripts, contributing to accelerated innovation and business enablement.
Assist in troubleshooting data pipeline issues and maintain documentation aligned with engineering best practices.
Proficient in Python and SQL with experience in cloud-based data platforms such as Snowflake or equivalent.
Familiarity with AWS services, especially S3 and Glue, and workflow orchestration tools like Airflow or Control-M.
Experience with RDBMS like Oracle, Postgres, or MSSQL and understanding of ETL and data security concepts.
Work Experience Required: Not explicitly mentioned in the JD.
Senior data engineer comfortable taking ownership of subsections of complex data platforms and applications.
Operational experience within cloud ecosystems, data pipeline development, and code versioning using GitHub.
Interested in learning investment management industry domain knowledge to align technical solutions with business goals.