Data Engineer

At HDR, we are committed to the principles of employment equity. We are an affirmative action and equal opportunity employer and consider all qualified applicants, regardless of criminal histories, arrest, and conviction records.

• Build and maintain batch and streaming ingestion pipelines from source systems into the enterprise data platform.
• Implement robust error handling, retries, and recovery patterns to improve reliability.
• Collaborate with platform teams on connectivity, access, and operational readiness.
• Develop transformation models using a layered structure (raw, conformed, curated) to separate concerns and improve maintainability.
• Use dependency management patterns to ensure correct build order and reproducible transformations.
• Leverage shared code and reusable components to standardize patterns, reduce duplication, and enforce consistent logic.
• Implement incremental processing where appropriate to reduce runtime and warehouse cost.
• Implement data quality tests (e.g., unique, , ) on critical models and key business entities.
• Configure and monitor source freshness expectations for important upstream datasets.
• Maintain model and column-level documentation; publish documentation and lineage to enable impact analysis and change management.
• Integrate transformations into CI/CD workflows (build, test, docs generation) before promotion to higher environments.
• Participate in code reviews, follow branching standards, and adhere to quality gates and approval processes.
• Support release and rollback practices to maintain stability and reduce risk.
• Tune transformations for performance and efficiency; partner with stakeholders to manage cost impacts.
• Support monitoring and alerting for pipelines and transformations; respond to incidents and perform root cause analysis.
• Document operational procedures and contribute to runbooks/playbooks.

• Hands‑on experience with dbt Cloud or dbt Core in Git‑integrated workflows.
• Experience with orchestration tools (e.g., Airflow, Dagster, Prefect) and scheduling patterns.
• Experience implementing CI/CD quality gates for data (tests, linting, docs artifacts).

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or equivalent practical experience.
• Minimum 3 years of experience in data engineering, data integration, or related roles.
• Proven SQL proficiency and experience building transformations and pipelines.
• Familiarity with cloud data platforms and modern ELT patterns.

Primary Location

Full‑time

Regular

May 27, 2026