Key skills
PythonSQLAIMachine LearningData EngineeringDatabricksAirflowGoogle CloudTerraformGitHub ActionsGitHubCI/CD
About this role
Role: Sr. Data Engineer
Location: Dallas, TX (Onsite role)
Duration: 12+ Months
Need to attend In person Interview
Need Only W2 candidates
Job Description:
As a Senior Data Engineer, you will build and optimize scalable data pipelines and models that power critical business insights. You’ll leverage cloud technologies, automation, and modern data engineering practices to transform complex datasets into reliable, highquality assets.
What you''ll do:
- Design and build scalable data pipelines and models using Databricks, PySpark, and SQL.
- Integrate and transform data from multiple sources with strong quality, observability, and governance.
- Orchestrate and automate workflows using Airflow and CI/CD pipelines in GitHub Actions.
- Develop and maintain infrastructure using Terraform and support DevOps tasks such as deployments, monitoring, and environment management.
- Optimize pipelines for reliability, performance, and cost across cloud environments.
- Collaborate with Product, Data Science, and Engineering teams to deliver reliable, scalable, and efficient data solutions.
What you''ll bring:
- Extensive experience in data engineering, including scalable pipeline development, data integration, and modeling.
- Strong proficiency in SQL, Python, PySpark, Databricks, and workflow orchestration with Airflow.
- Solid understanding of cloud platforms, especially Google Cloud Platform.
- Hands on experience with CI/CD using GitHub Actions and infrastructure automation with Terraform.
- Strong grounding in data governance, data quality, and compliance best practices.
- Ability to design resilient data architectures across warehouses, lakes, and streaming systems.
- Proven skill in translating complex business needs into effective data solutions.
- Familiarity with machine learning concepts and how they integrate with data engineering workflows.
- A passion for finding ways to integrate AI and LLMs into daily engineering
activities and products, while not compromising simplicity and code
maintainability.