Senior Analytics Engineer - Auto Integrate

Fleetio is a modern software platform that helps organizations manage their fleet operations. They are seeking a Senior Analytics Engineer to build and scale Auto Integrate's internal analytics infrastructure, focusing on data modeling, platform architecture, and collaboration with various stakeholders to enable data-driven insights.

Responsibilities:

• Enable self-service analytics for all team members by designing clean, intuitive data models and metrics through dbt, empowering employees to make informed, data-driven decisions
• Develop and refine custom data pipelines that ingest data from operational systems to our analytics platform, handling both streaming and batch data using third-party tooling and home-grown solutions
• Maintain and optimize the data platform infrastructure, focusing on data quality, ELT efficiency, and platform hygiene
• Architect and implement key components of the analytics infrastructure, such as BI, semantic layers, and foundational data warehouse
• Develop and maintain streaming data pipelines from a variety of databases and data sources
• Collaborate across business units to understand data needs and ensure required data is collected, modeled, and available to team members
• Document best practices and coach/advise other data analysts, product managers, engineers, etc. on data modeling, SQL query optimization & reusability, etc. Keep our data platform tidy by managing roles and permissions and deprecating old projects

Requirements:

• 5+ years of experience with a proven track record in data or analytics engineering
• Experience transforming raw data into clean models using standard tools of the modern data stack and a deep understanding of ELT and data modeling concepts
• Hands-on experience building and orchestrating ELT pipelines using Azure Data Factory
• Experience with Microsoft SQL Server
• Proficiency in Python and orchestration tooling like Prefect or Dagster
• Experience in designing, building, and administering modern data pipelines and data warehouses
• Experience with dbt
• Experience with semantic layers like Snowflake's semantic views, Cube, or Metricflow
• Experience with Snowflake, BigQuery, or Redshift
• Experience with version control tools such as GitHub or GitLab
• Experience with CI/CD and IaaC tooling such as GitHub Actions and Terraform
• Experience with business intelligence solutions (Metabase, Looker, Tableau)
• Excellent communication and project management skills with a customer service-focused mindset
• Experience with data marketplaces/private sharing technologies such as Snowflake Marketplace or AWS Data Exchange
• Experience with ELT tools such as Stitch or Fivetran
• Experience contributing to open-source projects
• Experience with streaming data and pipelines such as Kafka or Kinesis
• Experience with full-stack engineering