Manager, Analytics Engineering

Joining Beam Benefits Means:

• Working in a complex and dynamic business, simultaneously serving customers across employee benefits insurance product lines and growth and service channels
• Collaborating with a diversely skilled team to continuously improve
• Being empowered as an owner and expert
• Being motivated by improving how people access employee benefits

What You Will Do:

• Lead data lakehouse initiatives; own the strategy around how we move, store, govern and serve data internally and to our partners. 
• Lead coordination efforts with engineering partners to ensure stability and scalability of our Data Lakehouse, including defining standards, requirement gathering, testing, and timelines. 
• Serve as a primary data architecture resource who will help drive decisions on tooling, testing, and process to improve data quality.
• Support the analytics engineering tech stack, keeping pipelines running and maintaining infrastructure. 
• Manage a team of analytics engineers, coaching them in their desired career paths.
• Mentor analytics in their desire for increased technical proficiency. 
• Define and manage SLAs for data sets that support production services. 
• Design, build, and own data pipelines and warehouse systems that deliver information that drives the business forward.
• Ingest multiple internal and external systems into our data lake using batch and streaming concepts. 
• Implement an Incident Response Framework to handle situations that disrupt data availability to the business.
• Work with business domain experts to translate business processes and knowledge into data models that are understandable and used across the company.
• Partner with data analysts and engineering teams to build foundational data sets that are trusted, well understood, and aligned with business strategy in order to enable self-service through BI tools.
• Work with analytics and business teams to build predictive analytics solutions using machine learning.

What Skills Will Help You Be Successful:

• 5+ years of experience working as an analytics engineer, data engineer or data scientist (leading ETL work); 1+ year managing a team
• Deep technical proficiency in dbt, SQL, Dagster, Fivetran, Google Bigquery, Git Orchestration, Census, and Python; Data visualization tools (e.g., Looker), SalesForce, Docker, Buildkite, and Ruby are a plus. 
• Strong knowledge with data modeling methods and approaches (partitioning, star and snowflake, dimensional modeling) and capable of scaling over time.
• Experience coordinating with engineering teams to maintain stability of data pipelines. 
• Excellent communication skills; ability to work cross functionally with teams of various technical levels and drive a collaborative culture.
• Strong technical and people leadership skills. 
• Recent accomplishments working with object, relational, and columnar data stores such as Redshift. 
• Experience working in a Test Driven Development environment with Python, Java, or other data-oriented programming languages.
• Familiarity with data governance frameworks, SDLC, and Agile methodology.
• An understanding of containerization technologies and orchestration tools.
• Experience working in a healthcare technology environment is a plus.
• Also open to considering a Staff Analytics Engineering position if applicant is not interested in management track.