Senior Analytics Engineer, Pathstream
$120-165k
Salary dependent on location
SQL
Python
Tableau
Looker
Redshift
Snowflake
BigQuery
Git
dbt
Mid and Senior level
Remote from US
More information about location
Web-based platform for teaching tech skills
Be an early applicant
Web-based platform for teaching tech skills
101-200 employees
B2CEducationTraining
Be an early applicant
$120-165k
Salary dependent on location
SQL
Python
Tableau
Looker
Redshift
Snowflake
BigQuery
Git
dbt
Mid and Senior level
Remote from US
More information about location
101-200 employees
B2CEducationTraining
Company mission
To change the future of careers.
Role
Who you are
- You bring 4–6 years of professional analytics experience -with a track record of owning analyses and dashboards end-to-end that includes the messy front end: scoping ambiguous requests, asking the follow-up questions that reframe the work, and knowing when an analysis is actually answering the wrong question
- You've partnered closely with non-technical stakeholders and know the full arc of good analytical work — from the discovery conversation that surfaces what's actually being asked, through the judgment calls mid-analysis, to findings presented in a way that drives action rather than more questions
- You have strong SQL - comfortable writing complex queries, debugging joins, reasoning about performance, and working in a warehouse environment (Redshift, Snowflake, BigQuery, or similar)
- You are comfortable reading and writing SQL inside a version-controlled codebase. You see PR reviews as part of the craft, and you see modeling and transformation work as part of the analytics craft
- You have a working understanding of data modeling and schema design — you can reason about facts vs. dimensions, grain, normalization trade-offs, and when to build a new model vs. reshape an existing one. You don't need to have led a warehouse build, but you should have opinions about how data should be structured
- You bring a genuine business-intelligence mindset, with hands-on experience in a modern BI tool (Hex, Looker, Tableau, Mode, Sigma, or comparable) and an opinion on what makes a dashboard good
- You are a thoughtful collaborator on AI-assisted analytics workflows. You don't need to be an AI expert, but curiosity and willingness to learn matters — and you can speak from practical experience about what's worked and what hasn't in your own work
- You have hands-on experience with dbt or strong motivation to ramp quickly; working knowledge of Python is a plus
- You bring familiarity with version control workflows (git, PRs, code review) for analytics work, or are eager to develop them
- You take quality seriously — you build tests, you check your own work, and you understand that a trusted dashboard is worth more than a clever one
- You have demonstrated cross-functional partnership — with business stakeholders (PMs, ops leads, growth) and technical counterparts (engineering, product). You can run a discovery conversation, push back when a request is underspecified, and deliver something both sides trust
- You bring strong written and verbal communication and can adapt your message to the audience. You write clearly enough that an executive can act on your analysis without a follow-up meeting
- You are comfortable with ambiguity, shifting priorities, and making pragmatic decisions to unblock the business. You know when to push for precision and when "good enough, today" is the right call
- You invest in the people around you — through code review, mentorship, and the everyday work of helping a small team get better together
What the job involves
- Pathstream is seeking an experienced Senior Analytics Engineer to join our Data team and drive the next chapter of how we use data to make decisions
- This is a senior individual contributor role reporting to the Director of Insights & Operations
- We are looking for someone who has already built a strong foundation in stakeholder-facing analytics and the engineering craft that sits underneath it, and who now brings the judgment, range, and ambition to operate end-to-end across the analytics stack — from ambiguous business questions through to the data models and pipelines that answer them
- A core expectation of this role is the ability to advance Pathstream's AI-native data practices
- AI adoption is already deeply embedded in how we build software at Pathstream, and the data team is no exception
- We are looking for someone who not only embraces this approach but actively pushes the data team forward in adopting AI-assisted analytics workflows
- Partner with business stakeholders across Operations, Customer Success, Product, Growth, and Learning to scope analyses, define metrics, and answer the questions that drive decisions. Translate ambiguous, business-language requests into clear analytical work that holds up to scrutiny and leads to action
- Drive the analysis itself — bring judgment about what question is actually being asked, what the right analytical approach is, and what "good" looks like. Push back when a request is underspecified and shape vague asks into rigorous analyses
- Own dashboards end-to-end with a strong business-intelligence mindset — design, build, maintain, and iterate based on stakeholder feedback to make data products that people actually use. You'll work in Hex (our primary BI tool), but we're looking for BI craft and judgment, not Hex-specific experience
- Adapt your message to the audience — surfacing the action-oriented takeaway for an executive, walking through the details with a peer, and producing written analyses that hold up after you've left the meeting
- Bring a data engineering and data architecture mindset — think about what data models should exist, how data flows between source systems and the warehouse, how schemas connect, and where pipelines need to be reinforced. Partner on data modeling decisions and contribute to the warehouse (in our case, primarily through dbt)
- Take ownership of data quality and trust. Build tests into the models you work on, set up monitoring on the dashboards and pipelines that matter most, and respond when something breaks. The bar is "stakeholders should be able to trust what they see."
- Collaborate closely with engineering — partner with the product and engineering teams on event instrumentation, source data quality, schema changes, and anything else upstream that affects what's available for analytics downstream. Be the analytics voice in engineering conversations, and the engineering-aware voice in analytics conversations
- Help shape the long-term direction of the data team — beyond day-to-day analysis, contribute your perspective on where the data architecture and analytics practice should be heading. Weigh in on what we should be measuring, how we should be instrumenting and collecting data, what tools belong in our stack, and where we should be investing for the next year and beyond. You won't own these decisions alone, but you'll be expected to bring informed opinions and help drive them forward
- Lean into an analytics culture where AI is already central to how we work. We use modern AI tooling (Claude Code, agentic skills) heavily in our day-to-day, and we're actively building out how the data team uses it
- Explore how AI-assisted workflows can improve the analytics craft - for SQL development, dbt modeling, dashboard prototyping, exploratory analysis, documentation, and code review. Bring practical experience and curiosity rather than buzzwords
- Contribute to how the data team develops reusable patterns, skills, and guardrails for working effectively alongside AI systems
- Help raise the bar across the small data team — review each other's SQL and dbt code, share patterns, and pair on tricky analyses. Be someone teammates want to learn from
- Bring others along in your work. Make decisions and trade-offs visible so the rest of the team learns from them, not just from the outcomes
- Operate as a steadying presence when priorities shift, requirements change, or analyses don't go the way anyone expected. Help the team stay focused on the decisions the work is meant to support
Our take
Applicant Tracking Systems are frequently used by companies to filter out resumes that do not include essential skills. However, University degrees often focus on generalized skill sets as opposed to career-critical skills, resulting in many strong candidates slipping through the cracks.
Pathstream builds optimized digital skill programs for job seekers by partnering with companies and educational institutions, with programs designed in collaboration with companies including Salesforce, Facebook and Tableau. The startup's aim is to deliver courses in career-critical skill sets to ensure applicants have all the necessary skills relevant to their career path.
Pathstream believes that degrees in the US still focus too much on qualifications in antiquated skill sets. It does not want to replace educational institutes, but partner with them to teach platform-centric and industry-critical skill sets. Strong funding and a good initial reach will support this aim moving forward.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Led by a woman
Top investors
-9% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Jun 2023
$38.8m
LATE VC
Aug 2019
$12m
SERIES A
Total funding: $51.8m
Company benefits
- Disability, life insurance
- Flexible spending accounts
- Flexible vacation
- Commuter benefits
- 401(k)
- Team Activities
- Work from home opportunities
- Health insurance
Company HQ
Union Square, San Francisco, CA
Leadership
Eleanor Cooper
(Co-Founder & CEO)Worked at Morgan Stanley as an Investment Banking Analyst. Was a Private Equity Investment Associate at Energy Capital Partner, and New Venture Lead at Entangled Ventures.
Lauren Pizer
(Co-Founder & SVP of Learning Experience)Was a Special Projects Associate at Explore Schools, Teaching Team Member at Hasso Plattner Institute of Design, and Director of Student Experience at MissionU. Was also Case Team Leader at Entangled Ventures.
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