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Mid-level data engineer in metro with common skills but niche Prophecy requirement reduces applicant pool.
Core data engineering skills transfer across industries, though Prophecy specialization reduces portability slightly.
Explicit 2–3 years requirement plus mandatory PySpark and Prophecy skills enforce strict filtering.
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Design, build, and operate scalable ETL/ELT data pipelines (batch and real-time) to ingest, transform, and load data from multiple sources.
Engineer and maintain reliable data platforms including data lakes and data warehouses with operational resilience.
Implement system integrations via APIs, streaming, and data integration tools, ensure data quality, governance, security, and enable DevOps practices (CI/CD, orchestration, monitoring, production support).
2-3 years of experience in data engineering or related field.
Proficiency in Python, Spark (PySpark), Apache technologies, and advanced SQL for large-scale data processing and transformations.
Graduate degree in Computer Science, Data Science, or related field.
Experience with Prophecy pipeline development and deployment is mandatory.
Strong operational focus on building and maintaining scalable, high-availability data pipelines and platforms.
Proficient in core software engineering principles with hands-on expertise in PySpark pipeline engineering and production support.
Experienced in enabling DevOps for data including CI/CD, orchestration, scheduling, and troubleshooting in large-scale environments.