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Mid-level generalist data role at a well-known bank in metros increases applicant competition significantly.
Core Snowflake, ETL and SQL skills are highly transferable, though banking domain knowledge moderately matters.
Explicit 5+ years plus mandatory Snowflake/ETL/SQL and data modelling requirements raise screening strictness.
Build, maintain, test, and optimize scalable data architecture to enable effective data use for analysts and scientists.
Collaborate with core technology and architecture teams to develop data solutions and advocate for product development improvements.
Manage data platform cost levers and integrate new data sources using appropriate tooling to deliver customer value.
Minimum 5 years experience with data usage, dependencies, and extracting value from large scale data.
Proficiency in SQL development including complex stored procedures, functions, views, and data processing logic.
Experience with at least one ETL tool such as Informatica, IDMC, SSIS, or ADF.
Experience with a cloud data warehouse platform such as Snowflake or BigQuery.
Experienced in data modeling including conceptual, logical, and physical models indicating a strong understanding of data architecture.
Comfortable performing root cause analysis and issue resolution within data engineering environments following DevOps practices.
Effective communicator capable of engaging proactively with diverse stakeholders to build data knowledge and solutions.