Senior / Staff Data Platform Engineer, Choco
3-5 days a week in office
Enabling a sustainable food system
Be an early applicant
Enabling a sustainable food system
201-500 employees
Be an early applicant
3-5 days a week in office
201-500 employees
Company mission
Choco's mission is to lead a change in one of the oldest industries on the planet.
Role
Who you are
- We’re looking for a strong and experienced engineer with demonstrated technical leadership, deep infrastructure thinking, a delivery mindset, and the ability to navigate ambiguity. You know how to scale a data platform not just in volume - but in usability, reliability, and impact
- 5+ years in data engineering, platform engineering, or infrastructure roles
- Experience in technical leadership
- Ownership of production data pipelines, ideally in fast-moving or startup environments
- Proven experience with modern data stacks: dbt, Airflow, SQLMesh, SQL, Python
- Ingestion from heterogeneous data sources: APIs, databases, cloud storage, streaming events
- Experience with data warehouse and lakehouse engines (Databricks, BigQuery, Snowflake, etc.) and reverse ETL
- Strong system design skills
- Clear communication: you can explain technical choices and collaborate across teams
Desirable
- Experience with Kafka, stream-processing frameworks, Elasticsearch, or managing event-driven systems
- Exposure to ML or AI platforms, especially MLOps, evaluation pipelines, model observability, deployment
- Interest or experience in people management
- Familiarity with the food supply chain, logistics, or e-commerce data domains
What the job involves
- We are seeking a Senior / Staff Data Platform Engineer ready to scale data infrastructure at the heart of Choco.
- We’re now looking for an experienced, pragmatic, and hands-on Senior Data Platform Engineer to bring the next level of scale, reliability, and usability to our data systems.
- You’ll join a small, high-impact team that owns all of Choco’s data infrastructure: From ingestion and transformation to reverse ETL, ML feature pipelines, observability, and AI deployment tooling
- This is not a data janitor role. You’ll be designing systems, writing production code, shaping infrastructure decisions, and working closely with analytics, ML, and product teams. You’ll bring clarity to messy systems, and help us go from “data is available” to “data is a competitive advantage.”
- Analytics: Business dashboards, experimentation, product instrumentation
- Products: Reverse ETL into Postgres, DynamoDB, Kafka so that teams can build data-powered products
- Machine Learning and AI: We provide ML and AI models with historical data, memory and context. In addition, we support ML engineers in their workflow and infrastructure
- Design and build reliable, scalable pipelines for ingesting data from dozens of sources - internal databases (Postgres, DynamoDB), APIs (Salesforce, Stripe, etc.), and event streams
- Own the platform for data transformations, enabling analysts and engineers to ship production dbt models
- Shape our evolving infrastructure for Data quality, Data ownership & Data governance, MLOps, LLM observability, and AI delivery, supporting our AI engineers in building and scaling intelligent systems
- Tame complexity: create clear abstractions, refactor legacy pipelines, improve data discoverability and usability
- Drive engineering excellence: write high-quality code, automate operations, document best practices, mentor peers
- We strike a good balance between building solutions in-house and adopting tools. In this role, you will be expected to ship code on a daily basis
- Our Lakehouse is built on top of AWS S3, with files stored as Delta and Databricks SQL as our main SQL execution engine
- The tools we have adopted so far are: dbt, Airflow, Athena, Databricks SQL, PySpark, DynamoDB, Kafka, Python, Docker, MLflow, Looker, Unity Catalog
- We run on AWS and use the following AWS products: Glue, SNS, SQS, Lambda, Athena, EMR, Batch, Kinesis Firehose
Our take
The restaurant industry has seen vast technological innovations throughout the last decade, yet the state of supply chain ordering and administration does not reflect this. Restaurants are still using archaic paperwork to order from suppliers, and this has the tendency to become clunky, inaccurate, and result in food waste. Choco exists to improve this situation by connecting restaurants and suppliers through its food ecosystem management software.
Choco isn't the only company to notice the potential for disruption in this space, but it has taken a unique approach by providing bespoke inventory applications and analytical tools to both restaurants and suppliers. It has a large and rapidly growing userbase and its supply chain now links more than 30,000 businesses, with more than £1.2 billion in goods traded on its platform.
Choco raised large amounts of capital in several funding rounds and achieved unicorn status with a valuation exceeding $1 billion. It has eyes on expansion, currently working with clients across the U.S. and Europe but planning to begin operations in South America, the Middle East, and Asia in the near future.
Steph
Company Specialist at Welcome to the Jungle
Insights
5% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Feb 2023
$28.6m
LATE VC
Dec 2022
$37.7m
LATE VC
Total funding: $341m
Company HQ
Kreuzberg, Berlin, Germany
Leadership
Daniel Khachab
(CEO)Experienced as Global Venture Development Manager and CEO of Rocket Internet SE. Co-founded Choco as CEO in 2018.
Julian Hammer
(CMO)Before co-founding Choco freelanced in product & marketing with Ace & Tate, BuzzHire and UpLabs. Before that was Senior Venture Associate with EPIC Companies and the Head of Marketing Intelligence for Global Savings Group.
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