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Metro location, broad skill requirements, and a popular data-engineer title increase competition.
Core data engineering skills like cloud, Spark, and Kafka are highly transferable across industries.
Explicit minimum experience plus many mandatory cloud, streaming, and Spark requirements make shortlisting strict.
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Lead design and development of data pipelines and data products ensuring scalability, sustainability, and robustness.
Drive standards and prototypes for data frameworks to optimize efficient data processing and analysis.
Build automated reporting systems providing timely insights to support data-driven decisions.
Minimum 6 years of relevant work experience; typically 10+ years preferred.
Expertise with cloud-based data platforms like Snowflake and AWS; experience with data lakes and open table formats.
Proficiency in data ingestion and streaming tools such as Kafka, AWS Glue, Flink; experience with data storage formats like Iceberg and Parquet.
Strong background in Spark for data transformation, including streaming and performance tuning.
Experienced technical leader capable of defining long-term architectural direction aligned with enterprise strategy.
Proven capability in operational excellence, ensuring data system reliability, observability, and performance.
Hands-on experience driving strategic decisions balancing speed, cost, risk, and flexibility in large-scale cloud data environments.