Data Engineer Modern Cloud & Semantic Data Platform

Data Engineer – Modern Cloud & Semantic Data Platform

Location: Houston, Texas, United States (Onsite)

Job Type: Full-time / Contract

Experience Level: 9–13+ Years

Domain Focus: Energy / Oil & Natural Gas Midstream

About the Role

We are seeking a senior-level Data Engineer to design, build, and scale a modern cloud data platform centered on Snowflake and AWS. The ideal candidate combines strong core data engineering fundamentals with experience in enterprise data platforms, ontology-driven modeling, and governed data products.

In this role, you will lead strategic data initiatives leveraging Snowflake, AWS, Iceberg managed tables, Snowflake Catalog, Snowflake Horizon, Informatica, and dbt. You will translate business concepts into trusted, reusable data assets supporting advanced analytics, business intelligence, application development, and AI-enabled use cases across the energy sector.

Key Responsibilities

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  Data Pipeline Engineering: Design, build, and maintain scalable data pipelines for structured, semi-structured, and unstructured data.

  
  


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  Data Ingestion & Extraction: Develop ELT/ETL ingestion processes using Informatica, aligning with enterprise standards and existing infrastructure.

  
  


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  Transformation & Analytics Engineering: Build transformation logic using dbt, including modular models, automated testing, documentation, and deployment workflows.

  
  


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  Data Warehouse & Architecture: Design and manage core data structures in Snowflake as the central strategic enterprise data platform.

  
  


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  Cloud Infrastructure: Integrate AWS-based data services and infrastructure to support applications and governed data products.

  
  


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  Open Table Formats & Lakehouse: Support data architecture using Apache Iceberg managed tables, focusing on open table formats, interoperability, cataloging, and governed access patterns.

  
  


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  Governance & Metadata Management: Leverage Snowflake Catalog and Snowflake Horizon for metadata management, data discovery, lineage tracking, policy enforcement, and secure data sharing.

  
  


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  Ontology & Semantic Modeling: Support ontology-driven data modeling, entity definitions, taxonomies, business glossaries, and semantic mappings in collaboration with domain experts.

  
  


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  Data Architecture & Design: Translate domain and business concepts into logical/physical data models and reusable data products.

  
  


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  Data Quality & Observability: Implement validation rules, data quality checks, observability tools, and lineage controls.

  
  


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  Domain Use Cases: Support applications in news intelligence, asset intelligence, analytics, and AI/LLM integration (including Claude).

  
  


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  Security & Compliance: Ensure all solutions satisfy enterprise requirements for access control, security, privacy, and performance.

  
  

Required Skills & Qualifications

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  Experience: 9 to 13+ years of data engineering, data modeling, ETL/ELT pipeline design, and cloud platform development experience.

  
  


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  Domain Expertise: Experience in the Oil & Natural Gas Midstream industry or broader Energy sector.

  
  


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  Snowflake Expertise: Deep hands-on proficiency with Snowflake (data modeling, performance optimization, access controls, warehouse/lakehouse patterns).

  
  


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  Cloud Platforms: Hands-on experience building and supporting applications in AWS cloud environments.

  
  


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  Generative AI / LLM Integration: Practical familiarity with Claude or LLM workflows integrated into data platforms.

  
  


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  Ingestion Tools: Experience with Informatica (or similar enterprise ETL tools) for ingestion and extract-load patterns.

  
  


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  dbt & Analytics Engineering: Demonstrated hands-on experience using dbt for transformations, testing, and CI/CD workflows.

  
  


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  Open Table Formats: Knowledge of Apache Iceberg (managed tables, schema evolution, catalog-based access).

  
  


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  Data Governance & Architecture: Familiarity with data cataloging, lineage tracking, policy-driven data access, metadata management, and knowledge graph/ontology concepts (semantic modeling, taxonomies, business glossaries).

  
  


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  Programming & SQL: Advanced proficiency in SQL and Python (or another core data engineering language).

  
  


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  Soft Skills: Excellent communication, stakeholder management, documentation, and problem-solving skills.

  
  

Preferred Skills

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  Experience with Snowflake Catalog and Snowflake Horizon.

  
  


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  Building governed data products for advanced analytics and AI/ML applications.

  
  


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  Enterprise governance tools, particularly Informatica Governance capabilities.

  
  


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  Knowledge of RDF, OWL, SHACL, SPARQL, graph databases, or knowledge graph platforms.

  
  


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  Hands-on design of semantic layers, domain ontologies, and enterprise metadata models.

  
  


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  Modern DataOps practices: CI/CD, Git, automated testing, continuous integration for data pipelines.

  
  


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  Data observability, data contracts, and automated quality frameworks.