Data Engineer (No Sponsorship Available)

Heritage Construction + Materials•Indianapolis, IN

30d

About The Position

Build Your Career at Heritage Construction + Materials! We are 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)
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

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.