Senior Data Engineer

At HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas to work every day. As we foster a culture of inclusion throughout our company and within our communities, we constantly ask ourselves: What is our impact on the world?

Watch Our Story:' https://www.hdrinc.com/our-story'

Each and every role throughout our organization makes a difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world.

Position Overview

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 DevOps.

Key Responsibilities

Data Architecture & Pipeline Engineering

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 like Azure Data Factory, Oracle Integration Cloud, Terraform, Azure EventHub 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.

Snowflake Engineering

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.

Infrastructure, CI/CD & Automation

Automate infrastructure provisioning using Terraform.

Build CI/CD pipelines for data workflows using GitHub Actions, Azure DevOps, or similar tools.

Ensure strong engineering standards across versioning, testing, and automation.

Orchestration, Monitoring & Observability

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.

Leadership, Collaboration & Mentorship

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.

Preferred Qualifications

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 EventHub.

Strong understanding of CI/CD, DevOps 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.

Success Indicators

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.

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