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Mid-level, popular data-engineer role in Gurgaon with broad skillset requirements and moderate employer brand.
Core data engineering skills are transferable but Snowflake certification and domain specifics increase specialization.
Mandatory Snowflake certification, 2+ years Python/PySpark and top-tier degree increase screening rigidity.
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Build and maintain scalable data pipelines supporting analytics, reporting, and AI/ML use cases.
Lead migration of legacy data architectures to modern, cloud-based AI-ready data platforms with semantic layers for business-friendly data access.
Collaborate with business stakeholders, data scientists, and product teams to translate data requirements into technical solutions while ensuring data quality and governance.
2+ years hands-on experience with advanced Python and PySpark including performance tuning and complex query optimization.
Experience with modern data architectures and data warehouses such as Snowflake, Databricks, BigQuery, or Redshift.
Snowflake certification (SnowPro Core required; SnowPro Advanced preferred).
Bachelor’s or Master’s degree in Economics, Statistics, Engineering, or related quantitative field from a top-tier university.
Expertise in cloud-based, AI-ready data platforms, particularly Snowflake and modern data warehouse technologies.
Experienced in designing semantic layers and optimizing data workflows for advanced analytics and BI.
Effective collaborator across business and technical teams, capable of translating complex data requirements into scalable solutions.