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Tier-1 brand, mid-level generalist data role, metro location, and broad tech requirements increase applicant competition.
Core data engineering skills are transferable, though financial-Aladdin domain knowledge increases role specificity.
Explicit 5+ years requirement and mandatory Snowflake, Airflow, dbt, Python, and Azure experience raises selection strictness.
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Own the design, development, testing, deployment, and maintenance of Enterprise Data Platform components including automation of data pipelines and performance enhancements.
Use technologies like Airflow, Python, Snowflake, and dbt to manage data acquisition, ingestion, processing, orchestration, and data quality frameworks.
Provide L2/L3 support and contribute to system design decisions ensuring scalability, consistency, and operational stability post-release.
Minimum 5+ years experience as a data engineer.
Proficient in SQL, advanced Python programming, Snowflake or similar cloud-native databases, Airflow orchestration, and dbt transformation tools.
Experience with Azure services (especially ADLS) and exposure to real-time streaming platforms (e.g. Snowpipe Streaming, Kafka).
Bachelor's degree in computer science is strongly preferred.
Experienced in Agile development and capable of coordinating across multiple stakeholders through the software development lifecycle.
Strong troubleshooting skills demonstrated by root cause analysis and performance tuning expertise.
Comfortable working in a fast-paced, matrixed environment requiring collaboration and clear communication.