Job Opportunity Posted today

Data Modeler

Company
Teamware Solutions
Location
Bangalore

Job Description

Hiring: Data Modeler – Midstream Oil & Gas

Experience: 6–8 years

Notice Period: Immediately to 15 days

Location: India


Required Qualifications

  • 6+ years of data modeling experience (conceptual, logical, physical), including dimensional modeling and normalized/3NF design.
  • Direct experience in midstream oil & gas — hands-on exposure to at least one of: pipeline scheduling/nominations, volumetric measurement and allocations, gas/liquids balancing, terminal or storage operations, or regulatory reporting Strong SQL skills and experience modeling for a cloud data warehouse (Snowflake, Redshift, BigQuery, or similar).
  • Practical experience with dbt (or a comparable transformation framework) — understands how models translate into source()/ref() dependencies, tests, and documentation.
  • Solid grasp of Kimball-style dimensional modeling (star schema, slowly changing dimensions, conformed dimensions, factless facts) and when to use Data Vault or 3NF instead.
  • Experience with data modeling tools (erwin, ER/Studio, SqlDBM, dbdiagram, or similar) and producing clear ER diagrams for both technical and business audiences.
  • Comfortable working directly with business SMEs to extract and formalize business rules into a data model — this role requires translating ambiguous operational knowledge into structured schemas, not just implementing a spec handed to you.
  • Understanding of data governance fundamentals: metadata management, data lineage, data quality rules, and stewardship.


Preferred Qualifications

  • Experience with Informatica IDMC (or similar ETL/ELT and CDC replication tooling) and understanding of how ingestion patterns (batch vs. CDC) affect downstream model design.
  • Experience with Airflow or another orchestration platform, and how DAG design affects data freshness and dependency management for the models you own.
  • Exposure to medallion/lakehouse architecture (Bronze/Silver/Gold) and the tradeoffs of layering conformed business models vs. raw ingestion.
  • Prior experience in a data governance or data steward capacity.


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