Data Operations, Principal

About the Role

The Principal Data Operations builds and operates the systems that move Hut 8's business and operational data from source systems into reliable, secure, analytics-ready data products. This includes source integrations, API and SFTP ingestion, ETL (Airflow) orchestration, data transformation, warehousing, cloud infrastructure configuration, monitoring, data quality, and production support. This is an individual-contributor role.

Principal Data Operations candidates will deliver work within established patterns and grow their ownership of production systems. Senior candidates will lead complex technical initiatives, improve standards, and provide technical guidance through design and code review.

What You'll Do

• Translate business and stakeholder requirements into reliable, well-documented data pipelines and services.
• Build and maintain ingestion from APIs, SFTP endpoints, files, databases, and cloud services, including coordination with external providers.
• Develop and operate Airflow and Google Cloud Composer workflows, including dependencies, retries, backfills, and alerting.
• Model and deliver data across BigQuery, Snowflake, Cloud SQL/PostgreSQL, and Google Cloud Storage using dbt, data marts, and semantic-layer objects.
• Support the cloud infrastructure behind data products, including Cloud Run, container images, Artifact Registry, IAM, service accounts, and Secret Manager.
• Design pipelines for idempotency, safe reruns, recoverability, and failure containment, with freshness, reconciliation, schema, and completeness checks.
• Improve observability through logs, dashboards, alerts, and runbooks, and validate that downstream data products are complete and accurate.
• Own production support for data systems, resolving incidents through root-cause analysis and durable corrective actions.
• Apply least-privilege access, secure secrets management, and sensitive-data controls, and support access reviews and data-governance practices.
• Work within GitHub pull-request, testing, CI/CD, and change-management practices; at the Senior level, lead complex integrations, migrations, reliability initiatives, and technical reviews.

About You

• 3+ years of experience in data engineering, software engineering, DataOps, or a related field; 5+ years for Senior level.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
• Strong Python and SQL skills.
• Experience operating production data pipelines.
• Experience with Airflow or Google Cloud Composer.
• Experience with BigQuery, Google Cloud Storage, and Snowflake.
• Familiarity with Git, GitHub, pull requests, automated testing, and CI/CD.
• Linux and Bash familiarity.
• Experience integrating REST APIs, SFTP, scheduled files, or databases.
• Understanding of data quality, freshness, reconciliation, schema evolution, and monitoring.
• Strong communication and cross-functional collaboration skills.

Preferred Qualifications

• 3+ years of experience in data engineering, software engineering, or a related field.
• Strong Python and SQL skills.
• Experience operating production systems and data pipelines.

Nice to Haves

• Experience with dbt, data modeling, data marts, metadata, lineage, or semantic layers.
• Experience with Cloud Run, Artifact Registry, IAM, Secret Manager, Docker, or service accounts.
• Experience with Cloud SQL/PostgreSQL or time-series data.
• Experience with Grafana, Tableau, Metabase, or similar reporting tools.
• Experience with finance, operational telemetry, infrastructure monitoring, or other time-series data.
• Experience with data governance, access reviews, and sensitive-data handling.
• Experience leading technical initiatives or mentoring peers for the Senior level.