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Mid-level data engineer role with common skills and MNC brand attracts many qualified applicants.
Strong SAP and Snowflake expertise required makes cross-industry transfers difficult without domain experience.
Explicit 5–7 years requirement plus mandatory Snowflake and SAP integration skills tightens screening.
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Design and implement SAP data ingestion pipelines into Snowflake, including incremental loads and near-real-time ingestion.
Develop and optimize ELT/ETL pipelines and maintain curated dimensional and data vault models for cross-functional analytics.
Tune pipelines for performance and cost efficiency, apply data governance and security best practices, and collaborate with BI and business stakeholders to deliver scalable datasets.
5–7 years of data engineering experience with hands-on Snowflake development.
Experience integrating SAP data (S/4HANA/ECC/BW/HANA) into analytics or data warehouses.
Strong SQL skills with query optimization and performance tuning in cloud warehouses.
Bachelor's degree with 5 years or Master's degree with 3 years of related work experience.
Experienced in SAP functional domains (FI/CO, MM, SD, PP) to map business requirements to data models.
Skilled in advanced Snowflake features (Snowpipe, Streams, Tasks, Dynamic Tables) and production-grade pipeline orchestration tools (Informatica, ADF, dbt).
Familiarity with data modeling concepts (dimensional, data vault), CI/CD practices, and Python for automation and pipeline utilities.