Lead Data Analytics Engineer at Zwift

Read by 40 job seekers.

Remote - eligible US locations

Seniority Level: Mid-Senior

Location: Remote - eligible US locations

About the role and about You:

The Lead Data Analytics Engineer is a key role within Zwift's Data team, responsible for leading projects and acting as the main data business partner to multiple teams. The ideal person in this role will evangelize a data driven culture and deliver solutions and insights to Watopians every day. We are looking for someone with strong curiosity and sense of ownership, who is excited to operate cross-functionally to support better data analysis and governance. If this sounds exciting to you, then please don't hesitate to apply.

What you’ll do:

Partner closely with senior leadership to influence strategic decision-making. Support the definition of key success metrics, spearhead the design of rollout and measurement plans, and oversee in-depth performance analysis of new initiatives, campaigns, and critical company objectives
Produce high quality data models, dashboards and ad hoc reports to support business performance analysis and decision-making
Collaborate with the Data Engineering team and Software Engineers to produce new well-governed datasets, tools and products that will enable team members and internal customers to use data with confidence
Support teams to design, launch, monitor, analyze and report on A/B, multivariate and campaign incrementality tests.
Prioritize your workload and support team members to balance delivery of proactive and practical insights with a timely turnaround on ad hoc requests that are aligned to key company initiatives
Collaborate with data analytics peers with a range of experience levels

What we’re looking for:

Master's or advanced degree in a quantitative field
Outstanding track record with 5+ years' experience in a consumer facing, digital first business. Technology, gaming, ecommerce, or subscription businesses an advantage
Strategic thinker with a hands-on approach, able to manage competing priorities, deliver on key initiatives, and drive measurable results within a fast-paced, high-growth environment
Expertise in querying databases using SQL and building new gold-level datasets
Excellent knowledge of data visualization and analysis tools, such as Tableau, Amplitude and Databricks
Comfortable working with data and software engineers to craft, instrument and test new data models
Must be organized, self-motivated, resourceful, curious and proactive

Bonus points:

Experience with DBT and Analytics Engineering best practices

For All US Based Full-Time Positions:

The base salary for this position ranges between $106,500 to $135,000 annually. The base salary will be based on a number of factors including the role offered, the individual's job-related knowledge, skills, qualifications, and geographic location. In addition to base salary, Zwift is proud to offer a comprehensive and competitive benefits package for all eligible employees which also includes performance bonuses, equity, and a full range of medical, financial, and other perks and benefits.

How to stand out among the rest:

Your resume/CV is enough to show off your skills, accomplishments, and experience. However, if you choose to include a cover letter introducing us to your awesome personality, we will read that too.

We strongly believe that different backgrounds and ideas are a competitive advantage; we hire candidates of any race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, Veteran status, and any other status. Zwift is proud to be an Equal Opportunity Employer. If you have a disability or special need that requires accommodation, please let us know by emailing careers@zwift.com.

Zwift, Inc. is an Equal Opportunity Employer.

Estimated Salary range:

Our salary intelligence, powered by our AI algorithms, has calculated an estimated range for this position between $110,000 - $160,000 . Please note that the actual salary for this position may vary, as it is dependent on various factors including but not limited to experience, location, and market dynamics.

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