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# Senior Data Engineer - 1S6J022

- **Company:** Golden Goose Group LLC
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Query Performance, Airflow, Code Review, Information Systems, Continuous Integration, Data as a Services, Information Engineering, Python (Programming Language), Machine Learning, DataOps, Data Streaming, Cloud Platform System, Sql Optimization, Apache Spark, Backend, Information Technology, Apache Kafka, Cloud Optimization, Software Version Control, Databricks
- **Published:** October 22, 2026
- **Apply:** https://www.thejobnetwork.com/job/3b2a9efd-f894-4b9f-a106-b7405ba685dc/senior-data-engineer-sj

## About the Role

* Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience
 * 6+ years of data engineering, analytics engineering, or backend platform experience
 * Advanced SQL and Python skills with experience building production-grade pipelines
 * Experience with a major cloud platform and modern data services, warehouses, or lakehouse technologies
 * Working knowledge of orchestration, transformation, version control, CI/CD, testing, and data observability
 * Experience with Spark, Databricks, Kafka, dbt, Airflow, or comparable technologies preferred
 * Strong system-design, troubleshooting, documentation, and stakeholder communication skills

All applicants must be legally authorized to work in the United States without sponsorship and must already possess long-term work authorization.

## Description

* Design, build, test, and operate scalable batch and streaming data pipelines
 * Integrate data from operational technology, monitoring, asset, energy, financial, and enterprise platforms
 * Develop curated data models and reusable datasets for analytics, reporting, forecasting, and machine learning
 * Establish data-quality checks, observability, lineage, documentation, and incident-response practices
 * Optimize storage, orchestration, query performance, reliability, and cloud cost
 * Partner with analysts, software engineers, operations leaders, and subject-matter experts to define data products
 * Review code, mentor engineers, and improve engineering standards and deployment practices
 * Apply security, privacy, access-control, and governance requirements throughout the data lifecycle