Working knowledge of AWS services such as S3, Glue, Lambda, Athena, EMR, Redshift, and cloud-based data architectures.
Oil & Natural Gas Midstream domain experience (Mandatory).
Claude AI / Generative AI experience (Mandatory).
Qualifications:
Strong experience in data engineering, data modeling, ETL/ELT, and cloud data platform development.
Hands-on experience with Snowflake, including data modeling, performance optimization, access controls, and scalable warehouse/lakehouse patterns.
Experience working in AWS cloud environments.
Experience with Informatica or similar enterprise data integration platforms for extract-load and ingestion patterns.
Experience with dbt for data transformations, testing, documentation, and analytics engineering workflows.
Understanding of Apache Iceberg or open table formats, including managed tables, schema evolution, interoperability, and catalog-based access.
Familiarity with data cataloging, governance, lineage, metadata management, and policy-driven data access.
Understanding of ontology, semantic modeling, taxonomies, business glossaries, or knowledge graph concepts.
Strong SQL skills and experience with Python or another data engineering language.
Key Responsibilities:
Design, build, and maintain scalable data pipelines across structured, semi-structured, and unstructured data sources.
Develop data ingestion and extract-load processes using Informatica, aligning with enterprise standards and existing in-house capabilities.
Build transformation logic using dbt, including modular models, testing, documentation, and deployment workflows.
Design and manage data structures in Snowflake, with Snowflake positioned as the central strategic data platform.
Work with AWS-based data services and infrastructure, supporting applications and data products running in the organization's AWS environment.
Support data architecture using Iceberg managed tables, including open table formats, interoperability, cataloging, and governed access patterns.
Use Snowflake Catalog and Snowflake Horizon to support metadata management, data discovery, governance, lineage, policy enforcement, and trusted data sharing.
Collaborate with data architects, governance teams, analysts, application teams, and business stakeholders to define trusted data products.
Work with domain experts to understand business concepts, entities, relationships, and terminology.
Support ontology-driven modeling, including entity definitions, taxonomies, relationships, business glossaries, and semantic mappings.
Support data products and applications such as news intelligence, asset intelligence, analytics, and AI-enabled use cases.
Ensure data solutions meet enterprise requirements for security, privacy, access control, performance, and reliability.
Numbers & Facts
Location
Houston, TX
Skills
AWS Lambdaunmatched
Access Controlunmatched
Amazon Simple Storage Service (S3)unmatched
Amazon Web Services (AWS)unmatched
Apacheunmatched
Artificial Intelligence (AI)unmatched
Cataloguingunmatched
Cloud Computingunmatched
Data Managementunmatched
Data Modelingunmatched
Data Structuresunmatched
DataArchitect Data Modeling Toolunmatched
Database Extract Transform and Load (ETL)unmatched
Documentationunmatched
Electronic Medical Recordsunmatched
Enterprise Data Integrationunmatched
Enterprise Protectionunmatched
Informaticaunmatched
Interoperabilityunmatched
Metadataunmatched
Natural Gasunmatched
Oil and Gasunmatched
Ontologyunmatched
Performance Modelingunmatched
Performance Tuning/Optimizationunmatched
Privacy Controlsunmatched
Product Supportunmatched
Python Programming/Scripting Languageunmatched
SQL (Structured Query Language)unmatched
Scalable System Developmentunmatched
Snowflake Schemaunmatched
Software Administrationunmatched
Software Engineeringunmatched
Structured Dataunmatched
Taxonomiesunmatched
Testingunmatched
Unstructured Dataunmatched
Use Casesunmatched
Warehousingunmatched
Workflow Analysisunmatched
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