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Metro-based mid-senior Data Engineer role with common title but niche Databricks certification reduces candidate pool.
Core data engineering skills transferable, but financial services experience preference increases domain sensitivity.
Mandatory 7-10 years and Databricks certification plus domain-specific tech requirements make screening stringent.
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Develop and deliver large scale digital and data solutions for multiple customers, focusing on data ingestion and transformation pipelines.
Utilize ETL/ELT tools and various technologies including SQL, Python, Snowflake, and Amazon S3 to build high-quality data processing solutions.
Communicate complex technical concepts effectively to non-technical stakeholders and translate business requirements into technical implementations.
7-10 years of experience in data analysis or relevant roles, preferably in financial services.
Strong expertise in SQL including query optimization, window functions, and stored procedures.
Experience with ETL/ELT tools and data processing using Python.
Databricks certification required.
Experienced in implementing metadata-driven data pipelines for large-scale organizations.
Capable of independent problem solving and engaging with stakeholders across technical and business domains.
Familiar with cloud data platforms such as Snowflake and Amazon S3 and able to deliver end-to-end data solutions.