About the Role

We're looking for a data engineer who gets genuinely excited about query performance. You'll build pipelines that transform millions of Stripe transactions into analytics gold, optimize ClickHouse queries that run in milliseconds not minutes, and design warehouse schemas that scale effortlessly.

This is a rare chance to own the entire data infrastructure at an early-stage company. You'll architect systems from scratch, make architectural decisions that matter, and see your work power dashboards that thousands of SaaS founders check every morning. We work hard, move fast, but also know when to step back and optimize for the long term. And yes, we celebrate query improvements with the same enthusiasm as feature launches.

What You'll Do

Design and maintain our ClickHouse analytics database powering customer dashboards
Build ETL pipelines that transform raw Stripe data into clean, queryable models
Optimize complex analytical queries—making 30-second queries run in under 100ms
Design data warehouse schemas using star/snowflake patterns for analytics
Build data quality checks, monitoring, and alerting for pipeline health
Collaborate with backend engineers on MySQL → ClickHouse replication strategies
Own the full data stack: ingestion, transformation, storage, performance tuning

What We're Looking For

4+ years building production data pipelines and warehouse systems
Expert SQL skills—complex joins, window functions, CTEs are second nature
Experience with columnar databases (ClickHouse, BigQuery, Redshift, or similar)
Deep understanding of data warehouse design patterns and best practices
Strong query optimization skills—you can read EXPLAIN plans in your sleep
Experience building ETL/ELT pipelines at scale using modern tools
Programming skills in Python, PHP, or similar for data transformation scripts

Bonus Points

ClickHouse-specific experience—materialized views, distributed tables, replication
Built data pipelines for financial or payment data (Stripe, transactions, subscriptions)
AWS data tools experience (Lambda, S3, Athena, Glue, Kinesis)
Experience with dbt, Airflow, or other modern data orchestration tools
Understanding of dimensional modeling (Kimball methodology)
Early-stage startup experience—built data infrastructure from zero to one

Our Data Stack

Databases

ClickHouse
MySQL 8.0
Redis

Pipelines

Laravel Jobs
AWS Lambda
SQS Queues
Python Scripts

Infrastructure

AWS (S3, RDS, Lambda)
Docker
GitHub Actions
CloudWatch

Compensation & Benefits

→ Salary: £115,000 - £150,000 based on experience
→ Equity: 0.10% - 0.30% (early employee grant)
→ Health: Private medical insurance (Vitality or Bupa)
→ Time Off: 25 days + UK bank holidays + unlimited sick leave
→ Pension: 5% employer contribution
→ Learning: £2,000/year for courses, conferences, and certifications
→ Equipment: Latest MacBook Pro + accessories of your choice

How to Apply

Send your resume and a note about why you're excited about data infrastructure to careers [at] mowt.com with "Data Engineer" in the subject line.

We'd love to hear about data pipelines you've built, query optimizations you're proud of, or warehouse architectures you've designed. Bonus points if you include a before/after query performance improvement story. We respond within 3 business days.

Apply: careers@mowt.com

Data engineer