Back
Mid-level, generalist analytics role at a known global brand in metro location increases competition.
Analytics engineering skills transfer across industries but ERP and procurement domain experience increases specialization.
Explicit 4–6 years plus ERP and dbt/Databricks requirements create strict technical and domain filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and build analytics-ready data models and transformation pipelines using Databricks, dbt, SQL, and PySpark for enterprise data products.
Partner with business stakeholders to translate KPIs into reusable self-service datasets and develop enterprise dashboards and reports using Power BI or Tableau.
Manage ELT pipelines for data ingestion from ERP systems (SAP S/4HANA, Oracle) and other sources, and drive data governance, lineage, cataloging, and quality using tools like Collibra, Purview, and dbt tests.
4–6 years of experience in analytics engineering, data engineering, or BI development roles.
Proven delivery of at least 2–3 production analytics data products end-to-end.
Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, Engineering, Statistics, or related field.
Experience with enterprise ERP data (SAP S/4HANA, Oracle) and domain knowledge in procurement, supply chain, or finance analytics.
Experienced in bridging data engineering and business analytics to produce curated, trustworthy datasets that enable business decision making.
Familiar with modern data platforms and tools including Databricks, dbt, Power BI/Tableau, and data governance/catalog tools like Collibra or Purview.
Has exposure to finance and supply chain analytics areas such as spend analytics, supplier performance, demand planning, and understanding of AI/ML data pipeline requirements.