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Tier-1 brand, mid-level generalist title, metro context, and common data skills drive high competition.
Core data engineering, ETL, and cloud skills are highly transferable across industries.
Explicit 4+ years plus many mandatory data platform, cloud, and ETL technical requirements.
Lead and deliver moderately complex software engineering projects, including designing, coding, testing, and debugging within data platform domains.
Drive technical strategy planning and modernization efforts focused on enterprise-scale data environments and legacy tech migration.
Provide technical leadership, mentorship, and act as escalation point on issues, ensuring adherence to best practices and high code quality.
Minimum 4 years of software engineering experience.
Proficiency with Python, Spark, Iceberg, Hive, and strong SQL development and tuning skills.
Experience in large-scale distributed data systems, modern data warehousing/lakehouse architectures, and cloud platforms (Azure or GCP).
Work Experience Required: 4+ years explicitly mentioned.
Experienced in designing and operating enterprise-scale data platforms using modern data engineering and DevOps practices including CI/CD and automated code generation.
Hands-on with GenAI, Agentic AI, LLM adoption including building RAG architectures and integrating AI with data systems.
Able to function effectively in agile, fast-paced environments and collaborate across technical and functional teams for data platform modernization.