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Metro Bangalore location and popular data-engineer skillset, but seniority and specialized requirements moderate competition.
Core data engineering skills are transferable, though semiconductor manufacturing preference raises domain-specific fit needs.
Explicit 15-year minimum plus strong mandatory data-warehouse, PySpark and AWS technical requirements increase filter strictness.
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Lead design and development of secure, stable, and scalable data pipelines and data warehouse solutions across multiple global semiconductor manufacturing sites.
Act as subject matter expert on complex, cross-functional projects, providing technical leadership and guidance to junior data engineers and implementation teams.
Design data platforms and frameworks, evaluate access control processes for data security, and develop technical documentation supporting best practices.
Minimum 15 years of experience with data warehouse design, build, performance tuning, and optimization.
Strong programming skills with SQL and PySpark; experience with AWS services such as EMR, Redshift/Postgres.
Experience with cloud/ETL technologies including Databricks, Snowflake, Ab Initio; knowledge of additional programming languages like Python and Java.
Work Experience Required: 15 years minimum in data warehousing and related technologies.
Deep expertise in data warehouse architecture including dimensional modeling and ERD design, with strong analytical and data modeling skills.
Experience working in high-volume, complex database environments, preferably within semiconductor or high-tech manufacturing sectors.
Operating style focused on leading cross-functional technical projects and mentoring engineering teams; strong conceptual and documentation skills to capture complex data flows and business processes.