Senior Data Engineer​/Data Analyst; Databricks & Oracle ERP

Position Overview

We are seeking a high-caliber Senior Data Engineer / Data Analyst with a unique blend of modern cloud data engineering expertise and deep roots in Oracle ERP systems. In this role, you will architect, build, and optimize data pipelines that extract high-value financial, supply chain, and operational data from Oracle EBS or Fusion, transforming it within Databricks to drive enterprise-wide analytics.

If you are a hybrid engineer-analyst who can both write complex PySpark jobs and talk intelligently with business stakeholders about Oracle ledger tables, we want to hear from you.

• Data Pipeline Engineering: Design, build, and maintain robust, scalable batch and real-time ETL/ELT pipelines to ingest data from Oracle ERP (EBS or Cloud Fusion) into a Databricks Lakehouse environment.
• Data Analysis & Modeling: Analyze complex Oracle ERP schemas (FND, GL, AP, AR, PO, INV, etc.) to map, clean, and model data for downstream business intelligence and reporting.
• Performance Optimization: Tune complex SQL queries, optimize Databricks clusters, and manage Delta Lake tables to ensure maximum speed and cost efficiency.
• Cross-Functional Collaboration: Partner with finance, supply chain, and business analysts to translate complex business requirements into technical data models.
• Governance & Documentation: Maintain rigorous data documentation, data lineage, and security compliance protocols across cloud and on-premise data estates.

• Experience: 5 years of dedicated data engineering or data analytics experience, with a heavy emphasis on enterprise ERP data.
• Oracle ERP Ecosystem: Hands-on, deep technical knowledge of Oracle EBS (R12) or Oracle Cloud Fusion underlying database tables, schemas, and API extraction methods.
• Databricks Mastery: Proven experience building pipelines within Databricks using PySpark, Scala, or Spark SQL
  . Deep understanding of Delta Lake architecture.
• Advanced SQL: Exceptional SQL skills for querying, data manipulation, and performance tuning against massive relational datasets.
• Cloud Infrastructure: Familiarity with cloud data platforms (AWS, Azure, or Google Cloud Platform) supporting the Databricks environment.

• Analytical Mindset: Ability to reverse-engineer messy legacy data structures and transform them into clean, reusable data assets.
• Communication: Excellent verbal and written communication skills; comfortable presenting technical data concepts to non-technical business partners.
• Hybrid Flexibility: Ability to commute to our Houston, TX office on a hybrid schedule (specific in-office days to be discussed).

Interested? Email your CV to us.

Location:

Houston, TX (Hybrid)

Position Type:
Contract

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