Job Duties
We are implementing a strict Medallion Architecture to organize petabytes of industrial data. This role is for a Data Engineer who excels at transforming raw chaos into structured, queryable assets.
You will build and maintain the ELT pipelines that move data from "Bronze" (Raw) to "Silver" (Cleaned) and "Gold" (Aggregated). You will work with Delta Lake (On-prem/Databricks), Polars, and Airflow to ensure data quality and availability for Data Scientists and the Knowledge Graph.
What You’ll Do
Pipeline Development: Develop and maintain robust Airflow DAGs to orchestrate complex data transformations.
Data Transformation: Use Spark (when scale requires) and Polars to clean, enrich, and aggregate data according to business logic.
Architecture Implementation: Enforce the Medallion Architecture patterns, ensuring clear separation of concerns between data layers.
Performance Tuning: Optimize processing workflows (Polars/Spark) jobs and SQL queries to reduce costs and execution time; make intelligent decisions on when to use Polars vs. Spark.
Deployment & Operations: Manage code deployment to on‑prem and cloud infrastructure, including containerization and environment configuration.
Data Quality: Implement comprehensive data validation checks and quality gates between medallion layers.
Data Cataloging: Maintain the metadata and catalog entries to ensure all data assets are discoverable and documented.
The Technology Stack
Data Processing: Polars (primary for ETL), PySpark/SQL (for massive scale)
Compute: Single-node workers (Polars), Databricks/Spark clusters (when scale requires)
Qualifications
Must Haves: Complete Bachelor's degree in Computer Science, Engineering, or related.
Must Haves: 3+ years of experience in Data Engineering.
Must Haves: Strong proficiency in Apache Airflow and Databricks.
Must Haves: Experience implementing Medallion/Delta Lake architectures.
Must Haves: Strong SQL and Python skills.
Must Haves: Advanced English communication skills.
Good to Have: Experience with Unity Catalog or other governance tools.
Good to Have: Familiarity with dbt (data build tool).
Good to Have: Background in processing telemetry or sensor data.
Knowledge, Skills, and Abilities
The Structured Thinker: You love organizing data. You understand the importance of schemas, data typing, and normalization.
Quality Obsessive: You don't just move data; you test it. You implement checks to ensure no bad data reaches the Gold layer.
Pipeline Builder: You view data engineering as software engineering. You write modular, reusable code for your transformations.
Equal Opportunity Employer
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Location
Fully Remote position.
Requisition Number: 205556
Experience Level: Entry‑Level
Job Family: Engineering/Science/Technology
Product Service Line: Landmark Software & Services
Full Time / Part Time: Full Time
Employee Group: Temporary
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