Data Engineering and Analytics Manager

Spark is looking to bring on a manager to lead our Data function. Historically, the industry has had a lack of transparency, however, Spark is on a mission to change that and you can be a key part of the change by helping Spark and our customers wrangle, structure and draw valuable insights from a variety of data sources.

In this role, you will be responsible for all-things-data at Spark. You will work with data engineers to build out our data warehouse and implement technology that allows us to productionalize new data products for our agents. You will guide your team to take messy data from insurance carriers and standardize and automate the cleaning and processing of it. You will work with your team to build analytics infrastructure and dashboards, empowering Spark and our customers to make more data-driven decisions. Reporting to the Head of Engineering, you will collaborate closely with product, engineering, carrier relations, and other organizations across Spark to drive our data initiatives.

Key Responsibilities

• Hire, onboard, and mentor team members across data engineering, pipelining, and analytics
• Balance hands-on technical work with providing high-level guidance and mentorship to the team
• Drive the planning, prioritization, scoping and execution of the data roadmap
• Partner with product, engineering, carrier relations, and finance on strategic data initiatives, acting as the key point of contact for data-related needs
• Build and maintain scalable data infrastructure on our data stack in GCP using BigQuery, Dataform, Datastream, Cloud Composer, Metabase and Hex
• Architect and build pipelines to transform data from messy into structured and consumable for key agent features
• Automate and standardize manual data processes, ensuring efficiency and scalability, turning messy data into clean and valuable datasets
• Guide your team in providing BI insights and building and maintain dashboards that enable data-driven decision-making

Skills Knowledge and Expertise

• 5-8+ years in data engineering and analytics in a startup environment
• 1+ years in leading data teams in a management capacity
• Strong technical foundation in data engineering and infrastructure with a modern data stack (GCP or Snowflake, dbt, Airflow, Fivetran)
• Experience automating data workflows and cleaning messy data with modern tools (Dataform or dbt)
• Experience with BI tools and visualizing data (Metabase, Looker, Tableau or similar)
• Strong proficiency in SQL and Python
• Player/coach leadership style, balancing hands-on work with team management
• Strong project management, planning and prioritization skills
• The ability to both think strategically and tactically, architecting while executing
• Strong communication skills and experience collaborating on asks from cross-functional stakeholders

More about our data and the role

• The challenges with our data don’t come with number of rows but with complexity (messy data, not big data)
• Our data roadmap is defined by our customer and business needs. While we may need to build ML or AI in the future, there are no ML or AI features on our roadmap for 2025.
• This hire will be expected to manage 4 data team members in 2025
• Our current data stack is built in GCP using BigQuery, Dataform, Datastream, Cloud Composer, Metabase and Hex, however, we’re open to evolving the stack if there is value

Compensation