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Strong employer brand, common Data Engineer title, and mid-level (5+ years) experience increase applicant density.
Core data engineering skills are broadly transferable across industries despite FMCG domain preference.
Explicit 5+ years, required production data-pipeline experience and specific cloud/tool mandates create high filtering.
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Expand and optimize data and data pipeline architecture to support cross-functional teams.
Build, maintain, and orchestrate large scale data processing pipelines in production environments.
Collaborate with software developers, database architects, data analysts, and data scientists to ensure optimal data delivery architecture.
5+ years industry experience with 4-6 years in building and deploying large scale data processing pipelines.
Degree in Science or Engineering; Master's in Computer Science, Electrical Engineering, or related field preferred.
Strong experience with data lake, data warehouse, ETL/ELT, data marts, and SCD concepts; proficient in SQL/PLSQL and Python programming.
Experience with cloud platforms (Google Cloud Platform or Microsoft Azure) and orchestration tools like Airflow or Azure Data Factory.
Experienced in building data pipelines from ground up in production-scale environments.
Able to manage data from multiple structured and semi-structured sources, including SAP, BW, JSON, XML etc.
Familiar with analytics tools (BigQuery, Databricks) and cloud ecosystem certifications (GCP Professional Data Engineer or Azure Data Engineering).