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Job Description
Structured overview of role & requirementsAbout This Role
Independently design, build, and operate complex, production-grade data pipelines using Databricks and PySpark with focus on scalability and data quality.
Deploy pipelines via CI/CD, manage release lifecycle, support operational health including monitoring and incident response for business-critical workloads.
Mentor junior engineers through code and design reviews, and collaborate with cross-functional teams to deliver curated datasets for analytics.
Minimum Requirements
6+ years of data engineering experience with hands-on expertise in Databricks, Python (PySpark), and SQL.
Experience designing and delivering enterprise-scale production data pipelines (ETL/ELT) with strong focus on data quality and scalability.
Working knowledge of CI/CD pipelines, Git branching strategies, DevOps practices, and production support including monitoring and incident management.
Bachelor's or Master's degree in Computer Science, IT, or equivalent relevant experience.
Ideal Candidate Profile
Senior individual contributor comfortable owning end-to-end pipeline delivery with accountability for quality and operational health.
Strong DevOps mindset emphasizing automation, problem management, and continuous improvement to reduce recurring issues.
Experienced in collaborating across reporting, platform, and business teams and communicating technical trade-offs to technical and non-technical stakeholders.