Data Modeler

Elfonze Technologies

. Design conceptual, logical, and physical data models for midstream data domains, including pipeline scheduling and nominations, volumetric measurement and allocations, gathering and processing, terminal/storage inventory, tariffs and regulatory reporting, and commercial contracts .

Posted 9/22/2026full-timeRemote • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in data modeling, including conceptual, logical, and physical models, with a strong focus on dimensional modeling and data governance. Proficient in SQL and familiar with cloud data warehouses and transformation frameworks to support midstream oil and gas operations.

Highest-signal resume keywords

Data Modeling ExperienceSQL ProficiencyDimensional Modeling ExpertiseInformatica IDMC ExperienceData Governance Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingDimensional ModelingSQLData GovernanceSchema EvolutionData Quality RulesMetadata ManagementEntity Relationship DiagramsCloud Data Warehouse ModelingData Vault

Soft Skills

CollaborationCommunicationStakeholder EngagementBusiness Rule Formalization

Tools & Technologies

DbtInformatica IDMCSnowflakeRedshiftBigQueryErwinER/StudioSqlDBMAirflowDbdiagram

Industry Keywords

Midstream Oil & GasPipeline SchedulingVolumetric MeasurementRegulatory ReportingTariff SchedulesMaster Data ManagementData StewardshipMedallion ArchitectureLakehouse ArchitectureGas/Liquids Balancing

Tech Stack

Tools & technologies

AirflowAmazon RedshiftBigQueryCloudETLInformaticaSQLVault

About the role

Key responsibilities & impact

Design conceptual, logical, and physical data models for midstream data domains, including 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 with data engineering
Build and maintain dimensional models, including fact/dimension design, SCD Type 1/2 strategy, surrogate versus natural keys, and conformed dimensions
Partner with data engineers to translate models into dbt sources, staging models, and marts, and review pull requests for modeling and naming standards
Define and maintain the enterprise data dictionary, entity relationship documentation, and column-level metadata
Evaluate source systems ingested via Informatica IDMC/CDIR and dbt and model their reconciliation into a single conformed view
Lead data model reviews with commercial, scheduling, accounting, and regulatory stakeholders
Support master data management for assets, meters/measurement points, contracts, counterparties, and tariff schedules
Contribute to data governance, including naming conventions, modeling standards, data quality rules, and stewardship processes
Assess the impact of new data sources and business changes on existing models and propose schema evolution strategies that avoid breaking downstream consumers

Requirements

What you’ll need

5+ years of data modeling experience (conceptual, logical, physical), including dimensional modeling and normalized/3NF design
Direct experience in midstream oil & gas, with 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, including source()/ref() dependencies, tests, and documentation
Solid grasp of Kimball-style dimensional modeling, including star schema, slowly changing dimensions, conformed dimensions, and factless facts, and when to use Data Vault or 3NF
Experience with data modeling tools such as erwin, ER/Studio, SqlDBM, dbdiagram, or similar
Ability to produce clear ER diagrams for technical and business audiences
Ability to work directly with business SMEs to extract and formalize business rules into a data model
Understanding of data governance fundamentals: metadata management, data lineage, data quality rules, and stewardship
Preferred: Experience with Informatica IDMC or similar ETL/ELT and CDC replication tooling
Preferred: Experience with Airflow or another orchestration platform
Preferred: Exposure to medallion/lakehouse architecture (Bronze/Silver/Gold)
Preferred: Prior experience in a data governance or data steward capacity

Benefits

Comp & perks

Remote work arrangement