Klaviyo · klaviyo.com · checked today
Lead Strategic Finance & Analytics Engineer
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying.
Skills, with evidence
- Data modelling
You'll build scalable, production-quality forecasting systems, and you'll understand the financial mechanics well enough to make them useful for planning.
must have - Python
You're highly proficient in SQL and Python or R, with experience building production-quality analytical solutions, and you're familiar with dbt and modern analytics engineering practices.
must have - SQL
You're highly proficient in SQL and Python or R, with experience building production-quality analytical solutions, and you're familiar with dbt and modern analytics engineering practices.
must have - dbt
Partner with Analytics Engineering on reliable pipelines and dbt models that give forecasting a clean, trusted foundation.
must have - Machine learning
You have strong foundations in statistics and time series forecasting, and experience applying methods such as hierarchical, probabilistic, or machine learning approaches to business problems.
not practised here - AWS
You've worked with cloud data platforms and distributed processing systems.
not practised here - Cost & performance
We're looking for a Lead Strategic Finance & Analytics Engineer to build and maintain the models that forecast Klaviyo's recognized revenue and cost of goods sold (COGS).
- Failure handling
Monitor model performance over time , tracking accuracy and bias, detecting drift, and building challenger models to keep forecasts resilient.
- Dashboards & BI
Experience building self-service dashboards or forecasting tools used by Finance and Product partners.
not practised here - Governance & security
Experience establishing forecast evaluation frameworks or governance practices.
not practised here
Your plan
- The SQL screen: correct, then fast≈ 2 h
SQL
- Python: the data-wrangling round≈ 4 h
Python
- Data modelling: the round most people fail≈ 4 h
Data modelling · dbt
- Pipeline design: safe to run twice≈ 4 h
Failure handling
- Fourteen months of wrong numbersAdvanced
- The payload changed overnightAdvanced
- Delete me from everywhereAdvanced
- Ten times the traffic, for two weeksAdvanced
- Moving without a gapAdvanced
- Spark: read the plan Spark actually ran≈ 2 h
Cost & performance
- applyInPandas per country: what Spark ships to Python, and the native rewriteAdvanced
- Filters you wrote in the wrong place: where Catalyst moves themAdvanced
- snappy, gzip or zstd: measure the Parquet codec trade-off yourselfAdvanced
- Find the four suspects in a slow pipeline (one of them is innocent)Advanced
- A filter after a window function: pushed down or not?Advanced
- Say it out loud≈ 1 h
25 drills · Advanced + Intermediate≈ 17 hours
Not covered by the plan: Machine learning, AWS, Dashboards & BI, Governance & security.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 13 dremoved the moment Klaviyo closes it