The Role
Designs conceptual, logical, and physical data models for midstream oil and gas domains. Owns Bronze, Silver, and Gold layering, dimensional models, data dictionaries, metadata, lineage, and governance standards. Partners with data engineering on dbt implementation, evaluates source-system reconciliation, supports master data management, and leads model reviews with business stakeholders. Assesses schema evolution impacts and translates complex operational rules into scalable, documented data structures.
Summary Generated by Built In
This is a remote position.
Design conceptual, logical, and physical data models (ER diagrams, dimensional/star schemas, Data Vault where applicable) for midstream data domains — pipeline scheduling and nominations, volumetric measurement and allocations, gathering and processing, terminal/storage inventory, tariffs and regulatory reporting, and commercial contracts.
Own the Bronze → Silver → Gold layering strategy in partnership with data engineering: define what belongs in raw/staging vs. conformed business entities vs. presentation-layer facts and dimensions.
Build and maintain dimensional models (fact/dimension design, SCD Type 1/2 strategy, surrogate vs. natural keys, conformed dimensions across business units) for reporting and analytics consumption.
Partner with data engineers to translate models into dbt sources, staging models, and marts, and review PRs for adherence to modeling and naming standards.
Define and maintain the enterprise data dictionary, entity relationship documentation, and column-level metadata (business definitions, valid values, data lineage) for midstream subject areas.
Evaluate source systems ingested via Informatica IDMC/CDIR and dbt, and model how they reconcile into a single conformed view.
Lead data model reviews with business stakeholders (commercial, scheduling, accounting, regulatory) to validate that models correctly represent contracts, allocations, and volumetric relationships.
Support master data management for core midstream reference entities (assets, meters/measurement points, contracts, counterparties, tariff schedules).
Contribute to data governance: naming conventions, modeling standards, data quality rules, and stewardship processes.
Assess the impact of new data sources or business changes (new pipeline systems, acquisitions, regulatory changes) on existing models and propose schema evolution strategies that avoid breaking downstream consumers.
Required Qualifications
5+ 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.
Skills Required
- 5+ years of conceptual, logical, and physical data modeling experience, including dimensional modeling and normalized/3NF design.
- Hands-on midstream oil and gas experience in pipeline scheduling, nominations, volumetric measurement, allocations, gas/liquids balancing, terminal or storage operations, or regulatory reporting.
- Strong SQL skills and experience modeling for a cloud data warehouse such as Snowflake, Redshift, BigQuery, or similar.
- Practical experience with dbt or a comparable transformation framework, including dependencies, tests, and documentation.
- Knowledge of Kimball dimensional modeling, star schemas, slowly changing dimensions, conformed dimensions, factless facts, Data Vault, and 3NF.
- Experience with data modeling tools such as erwin, ER/Studio, SqlDBM, dbdiagram, or similar.
- Ability to work directly with business subject-matter experts to formalize business rules into data models.
- Understanding of data governance fundamentals, including metadata management, data lineage, data quality rules, and stewardship.
- Experience with Informatica IDMC or similar ETL/ELT and CDC replication tooling.
- Experience with Airflow or another orchestration platform.
- Exposure to medallion or lakehouse architecture and Bronze/Silver/Gold layering.
- Prior experience in a data governance or data steward capacity.
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The Company
What We Do
Elfonze Technologies is a Bengaluru-based technology and engineering services company that helps organizations modernize enterprise operations. Its offerings include Oracle ERP and enterprise applications, cloud and DevOps services, digital transformation, product engineering, connected supply-chain solutions, AI platforms, cybersecurity, staff augmentation, and managed solutions. The company serves global clients through IT consulting, technology delivery, and specialized supply-chain expertise, emphasizing innovation, operational excellence, and business-process improvement.
