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Remote mid‑level Databricks role with niche skills leads to moderate applicant competition.
Databricks and cloud data lake expertise moderately restricts cross‑industry transferability.
Explicit 5+ years Databricks requirement and mandatory Spark/Delta Lake skills increase filtering strictness.
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Lead migration and consolidation of data warehouse implementations into scalable data lake solutions on AWS using Databricks and Delta Lake.
Reverse-engineer and refactor legacy PL/SQL and SQL stored procedures into Spark SQL code within Databricks notebooks.
Build, optimize, and maintain ETL pipelines, data models, and data transformation processes while collaborating with data architects and cross-functional teams.
5+ years experience with Databricks including Spark SQL and Delta Lake implementations.
3+ years experience designing and implementing data lake architectures on Databricks.
Strong SQL and PL/SQL skills, plus proficiency in at least one programming language (Python, Scala, or Java).
Bachelor’s degree in Computer Science, IT, Data Engineering, or related field.
Experienced in migrating legacy data warehouses to modern cloud data lake architectures using Databricks on AWS.
Proficient in translating complex business logic from legacy SQL/PLSQL stored procedures into scalable Spark SQL code.
Capable of working in Agile environments with hands-on ETL pipeline development, data modeling, and performance optimization focus.