Senior Analytics Engineer

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About the Team

Analytics Engineers build upon the data foundation. We are looking for someone with expertise in metric development, data modeling, SQL, Python, and large-scale distributed data processing frameworks like Presto or Spark. Using these tools, along with first-class internal data tooling, you will transform data from data warehouse tables into critical data artifacts that power impactful analytic use cases (e.g. metrics, dashboards) and empower downstream data consumers. As an Analytics Engineer, you will sit at the intersection of data science, Product analytics and data engineering, and work collaboratively to achieve highly impactful outcomes. Data can transform how a company operates; high data quality and tooling is the biggest lever to achieving that transformation. You will make that happen.

Responsibilities:

• Understand data needs by interfacing with fellow Analytics Engineers, Data Scientists, Data Engineers, and Business Partners
• Architect, build, and launch efficient & reliable data models and pipelines in partnership with Data Engineering
• Design and implement metrics and dimensions to enable analysis and predictive modeling
• Design and develop data resources to enable self-serve data consumption
• Build tools for auditing, error logging, and validating data tables
• Define logging needs in partnership with Data Engineering
• Define and share best practices on metric, dimension, and data model development for analytics use
• Build and improve data tooling in partnership with Data Platform teams
• Be a technical expert on data model usage
• Own and review code changes to certified metric and dimension definitions
• Manage communication of data model updates and changes across organization
• Ensure data models are fully documented, and metrics and dimensions have clear descriptions and metadata

Minimum Qualifications:

• Passion for high data quality and scaling data science work
• 6+ years of relevant industry experience
• Strong skills in SQL and distributed system optimization (e.g. Spark, Presto, Hive)
• Experience in schema design and dimensional data modeling
• Experience in at least one programming language for data analysis (e.g. Python, R)
• Proven ability to succeed in both collaborative and independent work environments
• Detail-oriented and excited to learn new skills and tools
• Strong influence and relationship management skills

Preferred Qualifications:

• Experience with an ETL framework like Airflow
• Python, Scala, Superset preferred.
• Effective story-telling & articulation skills – ability to convert analytical output into clear, concise, and persuasive insights & recommendations for technical & non-technical audience
• An eye for design when it comes to dashboards and visualization tools
• Familiarity with experimentation and machine learning technique