- Company Name
- Octopus Energy
- Job Title
- Senior Analytics Engineer
- Job Description
-
**Job Title:** Senior Analytics Engineer
**Role Summary:**
Design, develop, and maintain a global analytics platform enabling consistent data modeling, self‑service insights, and reliable reporting across multiple business units. Lead the implementation of data mesh principles, CI/CD pipelines, and data governance to ensure high‑quality, discoverable metrics for producers and consumers worldwide.
**Expectations:**
- Advanced proficiency in SQL and Jinja.
- Hands‑on experience with dbt Core, Git, and a cloud data warehouse (e.g., Databricks, Snowflake, Google BigQuery).
- Ability to build scalable data models, dashboards, and automated testing frameworks.
- Strong understanding of CI/CD, monitoring, and data governance best practices.
- Collaborative mindset to consult with cross‑functional teams and document solutions.
- Nice‑to‑have: Python programming, Lightdash, Elementary, CircleCI, Airflow, Kubernetes, DuckDB, Spark, and knowledge of Kimball/OBT data modeling.
**Key Responsibilities:**
- Develop and maintain dbt models using a data mesh framework for diverse business domains.
- Create and support modern BI visualizations (charts, dashboards) for both detailed storytelling and live operational reporting.
- Implement comprehensive testing (e.g., dbt_expectations, Elementary) to ensure data quality and reliability.
- Define and enforce data governance and documentation standards to improve discoverability and consistency.
- Build and operate robust CI/CD pipelines for testing, deployment, and version control of analytics and BI assets.
- Design monitoring and alerting mechanisms to track analytics engine performance and data pipeline health.
- Provide technical consulting and training to data producers and consumers across global teams.
**Required Skills:**
- SQL (advanced)
- Jinja (advanced)
- dbt Core
- Git (version control)
- Cloud data warehouse (Databricks, Snowflake, GCP BigQuery, etc.)
- CI/CD concepts and tools (e.g., CircleCI)
- Data testing frameworks (dbt_expectations, Elementary)
- BI/dashboard tools (Lightdash or similar) – preferred
- Python – preferred
- Airflow, Kubernetes, Spark, DuckDB – preferred
- Data modeling methodologies (Kimball, OBT) – preferred
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field (or equivalent practical experience).
- Relevant certifications (e.g., Snowflake, Google Cloud Professional Data Engineer, dbt certifications) are a plus but not mandatory.