Senior Analytics Engineer

About the Role

As our first Senior Analytics Engineer, you’ll sit at the intersection of engineering and analytics, owning Clair’s data pipelines, modeling clean and trustworthy data sets, and collaborating closely with stakeholders across the entire organization (Product, Operations, and Finance, to name a few). You’ll play a critical role in defining our data architecture and improving data quality. Your primary stakeholder will be the analytics team. As you partner with data analysts and data scientists, you’ll design, develop, and deliver well-modeled, cost-efficient data models that power the impactful analyses that drive all decision-making at Clair. 

Some examples of what you’ll do…

• Model data from all of our products into flexible, trusted analytic reporting tables
• Migrate all of our data sources from Airbyte cloud to our self-hosted instance
• Support the data science team by building model feature pipelines
• Build new data management processes to maintain the integrity of production reporting environments
• Reduce Snowflake computing costs by identifying and optimizing key bottlenecks
• Implement a robust code style guide across the entirety of our dbt project(s) 

Key Responsibilities

• Own Clair’s ELT pipeline from start to finish and contribute to the development of best practices in modeling, testing, documentation, and observability
• Design, build, and maintain scalable data models using dbt that power analytics and business decisions
• Ingest and model data from new source systems to incorporate them into the data warehouse
• Partner with analysts, engineers, and business stakeholders to define metrics, data definitions, and governance standards
• Implement data governance, access control, and monitoring strategies across the entire data stack
• Identify data quality issues and lead efforts to resolve root causes
• Guide technical decisions as we scale the data function
• Occasionally support the analytics team with ad-hoc or high priority analysis. 

Qualifications

• 4-5 years of professional experience in the data analytics field
• Advanced SQL proficiency
• 2-3 years hands-on experience modeling data with dbt in a production environment
• Familiarity with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift)
• Familiarity with cloud data loading tools (e.g., Fivetran, Airbyte, Airflow)
• Strong understanding of data modeling concepts (dimensional modeling, Kimball, etc.)
• Experience with a scripting language like Python or R
• Experience working in a high-growth start-up environment
• Excellent communication skills, you can translate technical work into clear business value

Additional Details

Location: This is a hybrid position based out of New York City, you will be expected to come into the office at least three days a week (Tuesdays, Wednesdays, & Thursdays) with additional days on occasion for client meetings.

Compensation: The annual base salary for this role is $155,000-$160,000. The base pay for this role is determined using many factors, such as education, skills and experience and is reflective of Clair Series stage and size.  Base pay is only one part of Clair’s competitive total compensation package which includes equity, benefits and additional perks. The base pay range is subject to change and may be modified in the future.