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Tier-1 brand, metro location, and broad required skills drive high competition.
Core data engineering skills are broadly transferable across industries despite supply-chain knowledge preference.
Explicit 9+ years requirement plus mandatory data engineering tech stack enforces strict shortlisting.
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Lead advanced data ingestion, transformation, validation, and publishing processes for enterprise planning solutions.
Build and optimize scalable data pipelines integrating multiple data sources like Teradata, SAP ERP, SQL Server, Oracle using tools such as Python, PySpark, SQL, and SSIS.
Oversee production deployment, manage batch automation disruptions, provide technical leadership and code reviews for junior consultants to ensure best practices.
9+ years of professional experience in data architecture, data engineering, or related roles.
Proficiency with Python, PySpark, SQL, and workflow management tools like Airflow and SSIS.
Experience with large data volumes, data modeling, ETL processes, and cloud-based data platforms.
Advanced SQL skills and experience working with relational databases and version control platforms such as GitHub or Azure DevOps.
Experienced in managing end-to-end data integration projects involving diverse enterprise data sources and complex transformations.
Comfortable working in agile environments and capable of collaborating closely with functional teams to align technical integrations with business needs.
Capable of providing technical leadership, including code oversight and embedding industry standards for scalable and maintainable data architectures.