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- Tasks: Build and maintain analytics layers, ensuring clean and trustworthy data for stakeholders.
- Company: Join Flo Health Inc., a leading AI-powered digital health company for women.
- Benefits: Competitive salary, performance incentives, flexible working, and generous leave policies.
- Other info: Enjoy a 5-week paid sabbatical after 5 years and opportunities for professional growth.
- Why this job: Make a real impact in women's health while growing your skills in a dynamic environment.
- Qualifications: 5+ years in analytics engineering with strong SQL and Python skills.
The predicted salary is between 79000 - 95000 £ per year.
Join Flo Health Inc. as we build AI‑powered digital health for women. With 6M paid subscribers and a $1B valuation, we’re accelerating trust, privacy and clinical care at scale.
We’re looking for an analytics engineer who sits at the intersection of data engineering and analytics. You’ll bring engineering discipline to data modeling and transformation while ensuring data is clean, discoverable, and trustworthy so stakeholders can do their best work. A data analyst with strong SQL and Python who loves organizing and modeling data. A data engineer eager to get closer to business context and metrics.
What You’ll Do
- Build and maintain the analytics layer, including data transformations, marts, and semantic models.
- Partner with analysts and finance to define and implement core product and business metrics in our BI layer.
- Provide clean, well‑documented datasets and BI models that accelerate experimentation, product insights, and reporting.
- Apply validation, testing, and documentation standards to ensure high quality and trust in our data.
- Collaborate with the data platform team on ingestion, architecture, and performance optimization.
- Own data flows end‑to‑end, from event tracking definitions through ETL/ELT pipelines to ready‑made datasets and dashboards.
- Help define and enforce standards for how data models are stored, queried, and shared across the company.
Requirements
- 5+ years of experience in analytics engineering, data engineering, or data analysis with strong transformation ownership.
- Excellent SQL skills, including complex queries, window functions, and performance tuning.
- Solid Python skills for ETL/ELT, data wrangling, and workflow automation.
- Experience with data modeling techniques such as star schemas and dimensional modeling.
- Familiarity with modern data stack tools such as Databricks, Airflow, and Spark.
- Understanding of data warehousing concepts including ELT and optimization.
- Experience building metrics layers or standardizing business metrics is a plus.
- Knowledge of testing and version control practices (Git, CI/CD).
- Understanding of product and subscription metrics is an advantage.
- Experience with BI tools (e.g., Looker, Tableau, PowerBI).
Annual Salary Range: £79,000 - £95,000 GBP
What You’ll Get
- Competitive salary and annual reviews.
- Opportunity to participate in Flo’s performance incentive scheme.
- Paid holiday, sick leave, and female health leave.
- Enhanced parental leave and pay for maternity, paternity, same‑sex and adoptive parents.
- Accelerated professional growth through world‑changing work and learning support.
- Flexible office + home working, up to 2 months a year working abroad.
- 5‑week fully paid sabbatical at 5‑year Floversary.
- Flo Premium for friends.
Analytics Engineer employer: Flo Health Inc.
Contact Detail:
Flo Health Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving SQL and Python. We want to see how you tackle data challenges and make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on common analytics engineering questions. We recommend practising your problem-solving skills and being ready to discuss your past experiences with data modelling and transformation.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission at Flo Health.
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Analytics Engineer role. Highlight your SQL and Python skills, and any experience with data modeling techniques. We want to see how your background aligns with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and analytics, and explain why you’re excited about joining Flo Health. Let us know how you can contribute to our mission of building AI-powered digital health.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work that demonstrate your skills in data transformations, BI models, or any tools like Databricks or Airflow. We love seeing real-world applications of your expertise.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at Flo Health Inc.
✨Know Your Data Inside Out
Before the interview, make sure you’re well-versed in the data modelling techniques mentioned in the job description. Brush up on star schemas and dimensional modelling, and be ready to discuss how you've applied these in your previous roles.
✨Show Off Your SQL Skills
Prepare to demonstrate your SQL prowess during the interview. Think of complex queries you've written and be ready to explain your thought process. Practising performance tuning examples can also give you an edge.
✨Familiarise Yourself with the Tools
Get comfortable with the modern data stack tools like Databricks, Airflow, and Spark. If you’ve used them before, have specific examples ready to share. If not, do a bit of research to understand their functionalities and how they relate to the role.
✨Prepare for Collaboration Questions
Since this role involves partnering with analysts and finance, think about past experiences where you collaborated across teams. Be ready to discuss how you ensured data quality and trustworthiness while working with others.