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Metro locations, common Data Engineer title, and modest brand create moderate applicant competition.
Core data engineering skills are transferable, but OCI/AIDP and Oracle-specific experience raise industry fit sensitivity.
Explicit 8+ years requirement plus mandatory PySpark, OCI/AIDP, and MLOps skills increase filtering strictness.
Design, build, and operationalize scalable AI-ready data pipelines and platforms on Oracle AI Data Platform and Oracle Cloud Infrastructure.
Collaborate with enterprise customer technical teams and Oracle product teams to modernize data estates and accelerate Generative AI adoption.
Develop, optimize, and refactor PySpark and ETL workloads, and build APIs, SDKs, and automation frameworks to facilitate Oracle AI/data services adoption.
5 to 8 years of experience in data engineering, software engineering, or AI engineering with scalable data platform delivery.
Strong hands-on skills with Apache Spark, PySpark, Delta Lake, Python, SQL, and cloud data platforms (Databricks experience preferred).
Deep knowledge of Spark architecture, distributed systems, performance tuning, and ETL workload refactoring.
Location: Not explicitly mentioned; role locations include Hyderabad, Bangalore, Pune, Noida, Bengaluru, Mumbai, Chennai, Hyderabad.
Experienced in customer-facing consulting roles collaborating with enterprise technical and product teams in AI and cloud modernization.
Skilled in designing architectures for Lakehouse, Medallion, streaming, and real-time analytics with advanced data engineering technologies.
Familiar with DataOps, CI/CD, Infrastructure as Code, data security, governance, and has preferred OCI certifications and exposure to Generative AI/ML tools like LLMs, RAG, and MLOps.