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Senior Analytics Engineer

HubSpot LogoHubSpot
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Salary

$118,500 - $189,600

Location

Remote - USA

Product Operations is a fast-growing, global team of data-driven influencers, setting the standard for how data and analytics is used at HubSpot, and inspiring product teams to action.

The Senior Analytics Engineer serves as a force multiplier for the broader Prod Ops org: building and maintaining our highest value data assets; defining and implementing team strategy for analytics development processes; and enabling the team to operate with a consistent level of excellence as we scale in a remote, global environment.

In this role, you’ll get to:

  • Collaborate with technical and non-technical stakeholders, bridging the gap between business problem and technical solution
  • Own and champion Product Operations’ “crown jewel” data assets that answer HubSpot’s most critical operational questions, reinforcing them as Source of Truth across the organization
  • Develop scalable data models that enable performant analysis into Hubspot’s products and business
  • Curate, organize and document Product Operations data and reporting environments across Looker, dbt and Amplitude
  • Collaborate closely with Hubspot’s BI and Data Engineering teams to expand data access and availability
  • Codify and democratize best practices for SQL query optimization/reusability and reporting, leveraging HubSpot’s data assets, and analytics development within Snowflake SQL, dbt, LookML, and git
  • Define teamwide coding standards, documentation requirements and development processes (code reviews, testing requirements, etc)
  • Scope requirements with internal stakeholders and lead working groups to usher projects through their entire lifecycle while building clear roadmaps for cross-functional team members

We are looking for people with experience in the following areas:

**Basic Qualifications:

Development

  • Leading the technical execution of high complexity business intelligence and analytics projects in code with the use of CTEs, nested queries, or other similar techniques
  • Experience with complex datasets and computer science fundamentals, including software development lifecycle (SDLC)
  • Experience building and optimizing data pipelines, architectures and data sets; experience diagramming architecture and entity relationships with Lucidcharts (for example)
  • Understanding of multi-step ETL and ELT jobs / data pipelines and working with job scheduling systems, with an ability to reverse engineer and refactor existing technical projects

Analytics

  • Strong understanding of the analyst’s workflow as it relates to both structured and unstructured datasets
  • Exceptional ability to document technical designs
  • 3+ years of hands on experience experience with advanced SQL (writing and optimizing), cloud data warehouses (eg Snowflake, Redshift, Bigquery) and relational databases
  • Ability to collaborate through code-management/version control tools like GitHub Enterprise (for peer-reviews, feature branches, resolving conflicts and commits)

Team Enablement

  • Experience training and onboarding colleagues (especially at-scale, or in a remote-first or global environment)
  • Effective communication across multiple modes (video, wikis, decks, guided exercises) and a knack for choosing the best format for the task and audience at hand
  • Writing and reviewing end-user and technical documents, including requirements and design documents for existing and future data systems, as well as data standards and policies

Preferred Qualifications:

Development

  • Exposure to data pipeline and workflow management tools (i.e. Airflow, Google Cloud Composer, Luigi, etc)
  • Experience with script based analytic transformation tools (dbt, AWS Glue, Talend, etc)
  • 2+ years of experience with data quality and validation exercises in data science, business analytics, business intelligence (BI), or comparable big data “like” environments

Analytics

  • Experience with JSON Flattening and extracting internal elements
  • Conceptual knowledge of Looker (LookML, Looks and Dashboards) or equivalent BI visualization tool (e.g. Tableau, Qlik, Power Bi)

Team Enablement

  • Experience identifying and driving process improvements around data use to drive team effectiveness
  • Best practice definition: identifying the minimal set of rules for the greatest teamwide gains in clarity, accuracy, discoverability, and reusability
  • Patience, empathy, finding success in the team’s success

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