[Hiring] Data Engineer @Launchmetrics

Role Description

The Data Platform and Data Enrichment teams are in charge of making our unified database accessible, usable, enrichable and reliable for all our teams internally. The team owns the Lakehouse that powers Launchmetrics' data products — a Databricks-based platform built on Delta Lake, S3, and following a Bronze/Silver/Gold medallion architecture. This layer stores, enriches, and serves the media intelligence data behind Discover (our client-facing platform), Genie (internal tooling), and Delta Sharing. You'll work on a batch-first system that simulates real-time behavior using primitives like Change Data Feed, S3 event triggers, serverless compute, and liquid clustering.

This role plays a key part in our Tech & Product strategy, directly supporting company-wide objectives around customer retention, data trust, and the development of new AI-based insights.

What you'll do

• Design and build data pipelines (batch and near-real-time) using PySpark and Databricks, across the Bronze/Silver/Gold medallion layers
• Architect efficient Delta Lake table schemas — partitioning/liquid clustering strategy, schema evolution handling, and enrichment workflows
• Work closely with product, QA, and other data engineers to translate enrichment and search requirements into reliable pipelines
• Own code quality: structured PySpark jobs, unit tests (pytest), and adherence to team conventions
• Continuously improve pipeline reliability and cost efficiency (OPTIMIZE scheduling, retry/backoff logic, concurrency handling)
• Participate in cross-pod initiatives across the data platform

Technical Stack

• Languages: Python, PySpark, Typescript
• Data Platform: Databricks, Delta Lake, Delta Sharing
• Storage: AWS S3, MySQL
• Cloud: AWS (S3, Kinesis, Lambda, SQS, ECS, Step Functions, …)
• Tools: Jira, Databricks Asset Bundles, Serverless, Claude Code
• Versioning: Git, GitHub
• CI/CD: GitHub Actions
• Testing: pytest, Jest

Qualifications

• Engineer Degree or Master Degree in Computer Science and 3+ years of relevant work experience in full-stack development in a SaaS environment
• Strong Python and PySpark experience; comfort with distributed data processing at scale
• Experience with a Lakehouse architecture (Databricks, Delta Lake, or comparable — e.g. Spark on EMR/Glue)
• Familiarity with medallion architecture patterns (Bronze/Silver/Gold) or similar layered data design
• Ability to reason about schema evolution, partitioning/clustering strategy, and pipeline reliability (retries, idempotency)
• Ability to traverse logical sequences of either procedural or object-oriented code, abstracted or static - and understand it entirely
• Bright, energetic, highly motivated self-starter with experience in a fast-paced, results-oriented organization
• Ability to adapt, estimate workload, break down a task into logical steps, solve problems, self-improve and suggest new ways of improvement
• Last, but definitely not least: you speak, read, and write English fluently

How we hire

• Intro call with Talent Acquisition, to get to know each other (30 min).
• Meet & Greet with VP Software Development.
• Technical Interview, a live interview with a couple of Software Engineers.
• Team fit with the engineers and peers you'd build alongside.

Benefits

• Learning and development allowance
• Benefits package tailored to your location
• Flexible working arrangements with support to set up your home office
• Room to grow along whichever path fits you
• Remote-friendly, with hubs across our twelve markets

OUR COMMITMENT

Launchmetrics is proud to be an Equal Opportunity Employer building a diverse and inclusive workforce. If there is anything extra we can do to help you feel at ease during your interview process, please let the PeopleOps team member you’ll be meeting with know.