Data Engineer - Databricks (No Sponsorship Available)
About The Position
Heritage Construction + Materials is seeking a highly skilled Data Engineer to support the design, development, and implementation of our cloud data platform. This role is ideal for a Data Engineer who has experience in Databricks, cloud architecture, advanced data pipeline engineering, and building scalable, production-ready systems that support analytics, and enterprise-wide decision intelligence, with a potential to build and support AI/ML in the future. In this role, you will architect cloud data solutions, optimize data operations, and guide the evolution of our modern data ecosystem. You will work closely with cross-functional partners, including finance and operations, to deliver high-impact, reliable, and efficient data products and strategic data initiatives. This position requires U.S. work authorization.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field required
- 3+ years of experience in data engineering or cloud data architecture
- Expertise in Databricks or Snowflake Cloud Data Platforms
- Expertise with programming languages such as Python and/or SQL
- Experience with Python Data Science Libraries (PySpark, Pandas, etc.)
- Experience with Test Drive Development (TDD)
- Automated CI/CD Pipelines
- Linux / Bash / Docker
- Database Schema Design and Optimization
- Experience working in a cloud environment (Azure preferred) with strong understanding of cloud data architecture
- Experience with workflow orchestration (e.g., Databricks Jobs, or Azure Data Factory pipelines)
Nice To Haves
- Strong analytical and problem-solving skills
- Experience with programming languages such as Python, Java, R, or SQL
- Experience with Databricks or Snowflake Cloud Data Platforms
- Knowledge of statistical analysis and data visualization tools, such as PowerBI or Tableau
- Proficient in Microsoft Office
Responsibilities
- Design, implement, and maintain scalable data pipelines within a cloud data platform (Azure preferred)
- Build, optimize, and manage Databricks clusters, ensuring performance, cost efficiency, and reliable job execution
- Develop and maintain Delta Lake tables, pipelines, and storage patterns to ensure data quality, versioning, and performance
- Integrate Databricks with Azure services such as Azure Data Factory, ADLS, and Azure DevOps
- Support the implementation of a new cloud-based data warehouse, defining architecture, governance, and standards
- Build and automate CI/CD pipelines for data workflows using Azure DevOps
- Design and implement monitoring solutions using Databricks monitoring tools, Azure Log Analytics, or custom dashboards
- Collaborate with business and technical stakeholders to identify high-value data engineering and analytics opportunities and contribute to data governance initiatives
- Apply modern data engineering best practices to support advanced use cases involving NLP, predictive analytics, and automation
- Additional duties and responsibilities as assigned, including but not limited to continuously growing in alignment with the Company’s core values, competencies, and skills.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
