Senior Data Engineer

About HDR

At HDR, our employee‑owners are fully engaged in creating a welcoming environment where each of us is valued and respected, empowered to bring authentic selves and novel ideas to work every day. We foster a culture of inclusion throughout our company and within our communities, constantly asking:
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Automate infrastructure provisioning using Terraform.

The Senior Data Engineer is responsible for designing, building, and optimizing scalable data solutions that support analytics, operations, and enterprise decision‑making. This role owns full‑stack data engineering—from ingestion through transformation, modeling, orchestration, and delivery—leveraging Snowflake, SQL, Python, Azure, and Terraform. The Senior Data Engineer also mentors junior engineers, contributes to platform strategy, and ensures best practices in engineering, security, and Dev Ops.

• Architect, build, and maintain scalable, resilient data pipelines across batch and streaming workloads.
• Develop end‑to‑end data pipelines in our Snowflake data platform using technologies such as Azure Data Factory, Oracle Integration Cloud, Terraform, Azure Event Hub or equivalent services.
• Implement data transformations, data models, and testing frameworks using tools like Coalesce or Data Build Tool (DBT).
• Model structured and semi‑structured data for analytical, operational, and downstream consumption.

• Optimize Snowflake performance including warehouse sizing, clustering, micro‑partitioning, and query optimization.
• Build secure, scalable Snowflake schemas, tasks, pipes, and streams using Infrastructure as Code best practices.

• Automate infrastructure provisioning using Terraform.
• Build CI/CD pipelines for data workflows using Git Hub Actions, Azure Dev Ops, or similar tools.
• Ensure strong engineering standards across versioning, testing, and automation.

• Lead adoption of orchestration tools such as Airflow, Dagster, or ADF native orchestration.
• Develop monitoring, alerting, and data quality frameworks across pipelines.
• Improve system reliability, error recovery, and operational visibility.

• Mentor junior engineers and review code for quality, performance, and maintainability.
• Partner with analytics, engineering, and product teams to deliver high‑impact solutions.
• Influence data platform strategy and long‑term architecture decisions.

• Minimum 5 years of experience in data engineering.
• Advanced proficiency in SQL, Python, Terraform, and data modeling.
• Deep experience with Snowflake and Azure cloud environments.
• Strong experience with transformation tools.
• Experience with streaming architectures such as Kafka or Azure Event Hub.
• Strong understanding of CI/CD, Dev Ops principles, and Git‑based workflows.
• Excellent problem‑solving, communication, and leadership skills.
• Experience with orchestration frameworks such as Airflow, Dagster, or Prefect.
• Experience with containerization technologies including Docker or Kubernetes.

• Highly reliable, observable, and well‑documented pipelines.
• Improved Snowflake efficiency and optimized platform costs.
• Adoption of modern engineering standards across teams.
• Increased proficiency and independence among junior engineers.
• Strong cross‑team alignment on data architecture and best practices.

• Bachelor's degree in Computer Science, Management Information Systems, related technical area, or the relevant combination of education and relevant experience.
• 3-5 years of experience in administering systems‑related technologies.
• Excellent client service and interpersonal skills.
• Ability to analyze and design enterprise‑wide infrastructure technology systems.
• Ability to communicate with users and information technology professionals.
• Ability to work with vendors to request service and work through defective product issues.
• Self‑starter with the ability to handle multiple tasks and deadlines with…