Analytics Engineer Jobs
Analytics Engineer jobs are open across fintech, e-commerce, healthcare, and tech platforms, at every level from new-grad to staff and principal, with specializations in data modeling, dbt workflows, and data warehouse architecture. Find a role that fits from the openings below and apply directly.
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INTRODUCTION
Let’s face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship. We do. We can’t cram it all in here, but you’ll start noticing it from the first interview. Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you’ve ever met (yes, each with their own personal BetterUp Coach), and most importantly, work that matters. This makes for a remarkably focused and fulfilling work experience. Frankly, it’s not for everyone. But for people with fire in their belly, it’s a game-changing, career-defining, soul-lifting move. Join us and we promise you the most intense and fulfilling years of your career, doing life-changing work in a fun, inventive, soulful culture. If that sounds exciting—and the job description below feels like a fit—we really should start talking.
LOCATION
We are a hybrid company with a focus on in-person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include: Austin, TX; New York City, NY; San Francisco, CA; and the Washington, DC metro area. Please ensure you can realistically commit to this structure before applying.
ROLE AND RESPONSIBILITIES
We are looking for a Senior Analytics Engineer with experience building data modeling systems within a modern data stack, supported by intelligent data warehousing and adaptable business intelligence systems, to join our team. At BetterUp we believe data is critical to our success and this role on the Analytics Engineering team will be crucial to this strategy of delivering exceptional data products that will drive key business decisions. If you are passionate about helping people reach their potential, thrive in a fast-paced startup environment where you get to build the future, and love data then this is the role for you.
What You’ll Do:
- Architect, build and maintain efficient and reliable data products (dbt models, pipelines, Looker explores, visualizations, etc.) that enable data driven decision making.
- Build and maintain ELT pipelines from source systems to data warehouses.
- Influence strategy and drive execution of our analytical roadmap delivering self-service business intelligence at scale.
- Provide leadership and mentorship to other engineers fostering collaboration, knowledge sharing and a high bar for quality.
- Improve end users trust and confidence by driving best practices with regards to data discoverability, observability, lineage and stewardship.
- Contribute towards a robust data security strategy protecting sensitive information and content.
- Solve critical business problems through the application of programming, optimization, automation, and analytical skills.
BASIC QUALIFICATIONS
If you have some or all of the following, please apply:
- Minimum 5+ years of relevant experience in data engineering and/or analytics engineering
- Advanced SQL skills with 5+ years of deep experience with Snowflake or similar DB
- Expertise with data modeling and ETL/ELT (DBT preferred, pipeline development a plus)
- Seasoned developer (5+ years) within a modern business intelligence tool (Looker preferred)
- Experience applying software engineering principles (testing, version control, code reviews, CI/CD, etc.) in your working process, to scale analytical development
- Proven track record of working with data teams in a fast-paced, startup environment
- Proven track record of successfully working cross-functionally with both technical and non-technical stakeholders
- Solutions-driven and thrives when given ambiguous, open-ended problems
- Proven success driving projects through implementation to completion, including stakeholder education and onboarding
- Obsessed with data protections and privacy (i.e. PII, GDPR, FedRAMP, FIPS, etc.)
AI at BetterUp
Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We're looking for teammates who are excited to evolve alongside technology – people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation. During our interview process, you’ll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact.
As a Senior Analytics Engineer, You’ll
- Drive functional strategy for AI adoption, identifying transformational opportunities that create competitive advantage in how we build and scale our data products.
- Build scalable AI-powered systems that fundamentally change how analytical work gets done across multiple teams.
- Serve as a trusted advisor to leadership on AI capabilities, limitations, and strategic implications for our data platform.
- Establish governance frameworks and best practices for responsible AI usage at scale within the analytics function.
- Transform core data and analytics processes through strategic AI integration—including intelligent pipeline monitoring, automated data quality checks, and AI-assisted insight generation.
- Quantify AI impact on key data metrics and make data-driven recommendations for continued investment.
During our interview process, you’ll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact. We encourage all candidates to share examples of how they’ve used AI tools in their work—whether it’s AI-assisted SQL generation, LLM-powered data documentation, automated anomaly detection, or other applications. We view AI fluency as a complement to craft, not a replacement for it.
BENEFITS
At BetterUp, we are committed to living out our mission every day and that starts with providing benefits that allow our employees to care for themselves, support their families, and give back to their community.
- Access to BetterUp coaching; one for you and one for a friend or family member
- A competitive compensation plan with opportunity for advancement
- Medical, dental, and vision insurance
- Flexible paid time off
- Per year:
- All federal/statutory holidays observed
- 4 BetterUp Inner Workdays
- 5 Volunteer Days to give back
- Learning and Development stipend
- Company wide Summer & Winter breaks
- Year-round charitable contribution of your choice on behalf of BetterUp
- 401(k) self contribution
We are dedicated to building diverse teams that fuel an authentic workplace and sense of belonging for each and every employee. We know applying for a job can be intimidating, please don’t hesitate to reach out — we encourage everyone interested in joining us to apply.
BetterUp Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, disability, genetics, gender, sexual orientation, age, marital status, veteran status. In addition to federal law requirements, BetterUp Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
At BetterUp, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, residence location, as well as market indicators. The range below is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future. The base salary range for this role is as follows:
New York City and San Francisco: $176,000 - $220,000
Austin and Arlington: $158,000 - 198,000
Protecting your privacy and treating your personal information with care is very important to us, and central to the entire BetterUp family. By submitting your application, you acknowledge that your personal information will be processed in accordance with our Applicant Privacy Notice. If you have any questions about the privacy of your personal information or your rights with regards to your personal information, please reach out to support@betterup.co.
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Find Analytics Engineer JobsAnalytics Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple543

- Amazon465

- NVIDIA381

- Tata Consultancy Services (TCS)226

- TikTok188

Top Industries Hiring
- Technology & Software4,866
- Electronics & Hardware982
- Consulting & Professional Services924
- Banking & Financial Services649
- Investment & Asset Management469
What Employers Look For
The qualifications that appear most often in analytics engineer jobs.
- Proficiency in SQL and experience writing complex analytical queries
- Hands-on experience with dbt for data modeling and transformation
- Experience with a cloud data warehouse such as Snowflake, BigQuery, or Redshift
- Ability to work with data pipelines and orchestration tools like Airflow or Dagster
- Bachelor's degree in computer science, statistics, mathematics, or a related field
- Experience collaborating with data analysts and data engineers on cross-functional projects
Tips for Your Analytics Engineer Job Search
Show dbt and SQL project work
Hiring managers expect to see your data models, not just your job titles. Link to a public GitHub repo with dbt projects, documented schemas, or transformation logic you've built. Portfolios that show modeling decisions beat resumes that only list tools.
Tailor your resume to the data stack
Analytics engineer postings vary sharply by stack. Read each job description for the specific warehouse (Snowflake, BigQuery, Redshift) and orchestration tool (Airflow, Dagster) and mirror that language exactly in your resume's skills and project bullets.
Filter openings by data maturity stage
Early-stage companies need you to build pipelines from scratch. Mature data orgs need you to refactor legacy models. Knowing which environment you want before you apply saves time and helps you ask sharper questions during screening calls.
Apply early to roles that fit
Migrate Mate lists analytics engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for a take-home modeling exercise
Many analytics engineer interviews include a take-home where you model a raw dataset in dbt. Practice writing staging, intermediate, and mart layer models on public datasets so you can deliver clean, documented work under a time constraint.
Negotiate using scope, not just title
Analytics engineer leveling varies widely across companies. When negotiating, ask about data team size, model ownership, and roadmap influence. These factors define your actual role more than the title does, and clarifying them gives you real leverage.
Analytics Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most analytics engineers?
The companies hiring the most analytics engineers right now include Apple, Amazon, and NVIDIA, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of June 2026. Demand is concentrated at companies with large self-serve data programs and modern cloud warehouses.
How many analytics engineer jobs are remote?
About 28% of analytics engineer openings are fully remote or hybrid as of June 2026, making it one of the more remote-accessible technical roles. Data modeling and dbt-heavy work tends to be the most remote-friendly sub-area, while roles that require close collaboration with embedded business teams more often require on-site presence.
How do you become an analytics engineer?
Start by building strong SQL skills and learning dbt on a public dataset you can share. Get comfortable with one cloud data warehouse, then practice modeling raw data into clean, documented layers. Build a portfolio project that shows staging, intermediate, and mart models. Apply to junior or data analyst roles at companies with modern data stacks to get your first hands-on production experience.
How do you get hired as an analytics engineer with little experience?
Focus on demonstrating modeling judgment rather than years on the job. Build a dbt project on an open dataset, document your decisions in a README, and publish it publicly. Highlight any SQL work from analyst or engineering roles. Many teams hire candidates with strong SQL and analytical foundations and train them on the specific stack, so framing your background around data thinking helps.
What does the analytics engineer interview process look like?
The process typically starts with a recruiter screen focused on your background and the data stack you've used. A technical phone screen follows, often involving live SQL or a short modeling question. Most companies then assign a take-home exercise where you model a raw dataset in dbt. Final rounds include a technical deep-dive with the data team and a cross-functional conversation with stakeholders or analysts you'd support.
Where can I find and apply to analytics engineer jobs?
You can find and apply to analytics engineer jobs on Migrate Mate, which lists current openings from across the United States. Find roles that fit your experience, stack, and preferred work arrangement, then apply directly to each listing.
See All 12,213+ Analytics Engineer Jobs
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