Senior Analytics Engineer
About the Role
You will mature and scale the analytics data ecosystem by designing and optimizing pipelines and data models, implementing testing and observability, and improving performance and reliability. You will partner with data scientists, data engineers, product, and business teams to deliver production-ready datasets and dashboards. You will establish data quality solutions, troubleshoot performance issues, drive adoption of modern data tools and workflows, and share on-call responsibility for analytics infrastructure.
Requirements
- 8+ years of experience in analytics engineering, data engineering, or data science focused on scaling analytics workflows
- Strong experience across the Data Engineering lifecycle including ETL, data model design, infrastructure, data quality, and architecture
- Deep proficiency in SQL and experience building modular data models with dbt or equivalent in production
- Strong software engineering fundamentals with experience in Python, CI/CD pipelines, and automated testing
- Proficiency in defining robust and scalable data models using best practices
- Experience using LLMs and enabling AI through high quality data infrastructure
- Hands-on experience with cloud data warehouses and infrastructure such as Snowflake, BigQuery, or Redshift
- Experience with data orchestration tools such as Airflow, Dagster, or Prefect
- Proficiency building dashboards with Looker, Tableau, Power BI, Plotly, or similar
- Excellent communication skills with the ability to explain complex technical concepts to non-technical audiences
Responsibilities
- Lead development and optimization of analytics pipelines and data models
- Define and implement analytics engineering best practices (testing, observability, versioning, documentation)
- Improve scalability and maintainability of the analytics data ecosystem
- Partner with data scientists, data engineers, product, and business teams to deliver production-ready datasets
- Establish and maintain data quality solutions
- Investigate and resolve performance and reliability issues
- Drive adoption of modern data tools, orchestration, and workflows
- Participate in shared on-call responsibilities for analytics infrastructure