Analytics Engineer
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Job Description
Analytics Engineer building DoiT’s governed data platform for a global cloud technology company. Developing reliable models, pipelines, governance, and integrations across business domains.
Responsibilities:
- Share ownership of the data platform’s engineering, including model changes, engineering backlog, data source onboarding, CI/CD maintenance, and infrastructure operations
- Build, test, and maintain data models and pipelines powering dashboards, finance and investor reporting, and the AI analytics layer across 15+ business domains
- Provision and configure BigQuery datasets, views, GCS buckets, and IAM permissions through Terraform
- Onboard ingestion destinations, manage access controls, and handle schema drift on source tables
- Own and expand RBAC implementation and maintain data catalog metadata and documentation
- Improve platform reliability through stronger testing standards, observability, and alerting
- Support Airflow orchestration and scheduling, including troubleshooting dbt build failures in Cloud Composer
- Build and maintain Python-based Fivetran SDK connectors with pagination, rate limiting, error handling, and automated tests
- Partner with BI analysts to turn ambiguous questions into well-modeled, trustworthy datasets
- Raise engineering practices through code review and shared standards
- Use modern AI tooling to draft code and accelerate routine work
- Report to the Head of Business Intelligence and collaborate with BI analysts, engineers, and business partners
Requirements:
- 3–5 years in analytics engineering, data engineering, or BI engineering
- Strong SQL and data modeling skills
- Professional experience building and maintaining dbt projects, including packages, macros, incremental strategies, snapshots, seeds, and CI/CD
- Experience with staging → intermediate → mart patterns, deferred builds, state comparison, and slim CI
- Software engineering discipline with version control, code review, automated testing, and CI/CD
- Strong drive to automate repetitive manual work
- Ability to debug data issues to their root cause and consider freshness, volume, duplicates, and late-arriving data
- Ability to translate business needs into data requirements and work with non-technical stakeholders, including Finance
- Comfort navigating multiple repositories across transformation, data infrastructure, orchestration, custom connectors, and cloud resources
- Proven track record of using AI coding tools in daily workflow
- Independence in a remote, global team, with clear written communication and discipline to document work
- Fluent written and spoken English; other languages are an advantage
- Bonus: experience with BigQuery, Fivetran, Apache Airflow/Cloud Composer, or AWS/Azure equivalents
- Bonus: data catalog or data observability tooling experience
- Bonus: Git-based CI/CD workflows for data projects
- Bonus: Terraform for data infrastructure
- Bonus: Python for REST API data integration
- Bonus: dbt build lifecycle, BigQuery performance tuning, Docker, Kubernetes, SQLFluff/pre-commit, or SaaS source systems
Benefits:
- Unlimited Vacation
- Flexible Working Options
- Health Insurance
- Parental Leave
- Employee Stock Option Plan
- Home Office Allowance
- Professional Development Stipend
- Peer Recognition Program
- Remote work and schedule flexibility
- Opportunities to develop skills professionally and personally
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