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Tier-1 brand, metro location, and mid-level generalist data role increase applicant competition.
Data engineering skills transferable, but financial domain tooling and compliance raise moderate industry specificity.
Explicit 5+ years and mandatory Snowflake/Airflow/dbt/Python skills make shortlisting highly selective.
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Design, develop, test, deploy, and maintain core Enterprise Data Platform components focusing on data pipelines, orchestration, ingestion, and quality frameworks.
Automate data workflows and provide L2/L3 support for technical and operational issues related to the data platform.
Coordinate with product managers, data owners, and platform teams throughout the SDLC for performance tuning and scalability enhancements.
At least 5+ years of experience as a data engineer.
Strong proficiency in SQL, Python, Snowflake (or similar cloud-native database), Airflow, and dbt.
Experience with Azure services (especially ADLS) and real-time streaming platforms like Kafka or Snowpipe Streaming.
Bachelor's degree in computer science is strongly preferred.
Proven ability to design and implement scalable, performant data engineering solutions using modern cloud-native and orchestration tools.
Experience working in agile environments within matrixed organizations with multiple stakeholders.
Strong troubleshooting and root cause analysis skills for complex technical and operational issues.