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Manager – Analytics Engineering
| Company | Beam |
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| Location | Columbus, OH, USA |
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| Salary | $150000 – $175000 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Senior |
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Requirements
- 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.
Responsibilities
- 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.
Preferred Qualifications
- 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.
