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Open nowPosted 7 days ago

Senior ML Data Engineer

Ønskeskyen

Where
Denmark
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Your applicationOpen nowSenior ML Data EngineerØnskeskyen · Denmark

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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 7 days ago

The posting

**About GoWish, Ønskeskyen ☁️

**At GoWish, we’re building the world’s leading wish-list and social shopping platform - a place where you can make a real impact and have fun doing it.

We’re on a mission to reinvent gifting for millions. We win together, driven by curiosity, ownership, and bold ideas that turn into real products. We experiment cross-functionally, push for excellence, and keep things playful as we grow - together.

**Team & Role Overview

**We are looking for a systems-minded Senior ML Data Engineer to own the offline-to-online feature infrastructure that powers our real-time recommendation and search engines at scale. You will be building the low-latency data syncs and feature-serving layers that bridge our analytical warehouses with operational databases, caches, and Feature Stores. This is a role for a performance-driven engineer who excels at pipeline orchestration (Airflow, dbt), Infrastructure as Code (Terraform, Docker), and database tuning, ensuring our recommendation systems receive reliable data under strict low-latency SLAs. If you thrive on solving complex data synchronization challenges, scaling operational storage for millions of users, and acting as the operational bridge between Data Science and Backend Engineering - you will play a critical role in powering our product's core ML capabilities.

**What You'll Do

**

  • Offline-to-Online Feature Pipelines: Build and operate resilient feature pipelines syncing transformed data from analytical warehouses (e.g., BigQuery) into operational storage layers (e.g., AlloyDB, Redis, Feature Stores) to serve real-time ML recommendation models at scale.
  • Pipeline Orchestration and Transformations: Design, test, and maintain robust Apache Airflow DAGs and modular dbt transformations to automate end-to-end data ingestion and feature generation under strict low-latency SLAs.
  • Infrastructure as Code and Reliability: Provision, scale, and automate cloud data infrastructure using Terraform, Docker, and CI/CD pipelines, implementing automated data quality testing and monitoring across all feature syncs.
  • Cross-Functional System Design: Partner directly with Data Scientists and Backend Engineers to define online/offline feature contracts, optimize database schemas for sub-second queries, and eliminate training-serving skew for millions of active users.

**What we’re looking for 🌟

****We Imagine That You Have

**

  • 4+ years of experience
  • Operational Data Pipelines: Proven experience moving batch features from analytical warehouses (BigQuery, Snowflake) into low-latency online stores (AlloyDB, Redis, Feature Stores) to serve real-time ML recommendation models.
  • Infrastructure as Code (IaC): Deep hands-on experience provisioning, scaling, and managing cloud data infrastructure using Terraform, Docker, and modern CI/CD automation pipelines.
  • Pipeline Orchestration & Transformations: Strong track record building, scheduling, and maintaining workflow orchestrations (e.g., Airflow, Dagster) and modular data transformation frameworks (e.g., dbt).
  • Database Performance Tuning: Advanced SQL skills across both OLAP and OLTP systems. Ability to optimize schemas, indexing, partitioning, and queries.

It is further seen as an advantage to have experience with:

  • Production Feature Management: Experience managing Feature Stores (e.g., Feast, Tecton) or low-latency key-value stores (e.g., Redis) to serve online ML features with zero training-serving skew.
  • Real-Time OLA): Experience with ClickHouse, Pinot, Druid or others for ultra-fast aggregations over live event streams.
  • Event Streaming: Hands-on experience with streaming tools like GCP Pub/Sub, Kafka, or Flink for real-time feature updates.

Why GoWish should sit at top of your career wish list 💙

At GoWish, we believe great work comes from people who feel energized, supported, and excited to show up every day. That’s why we’ve built a workplace where celebration, growth, and genuine enjoyment are part of the journey - not perks on the side.

Take your birthday off with Happy Birthday Leave, enjoy 30 days of vacation to fully recharge, and join a team that fills the year with events and playful happenings. We invest in your future with pension and insurance, fuel your days with a weekly lunch scheme, and keep you going with unlimited snacks and sodas - because work should feel good.

At GoWish, you don’t just build great products. You build a great work life.

**Practical information

**We collaborate in a flexible hybrid setup, with most of our magic happening at our bright, modern office in Østerbro - perfectly placed between Nordhavn and Østerport Station. We’re ready for you to join us as soon as you are.

👉 Ready to help shape a platform that already empowers 18+ million users (and counting)? Join us at GoWish - and let’s build the future of data-driven innovation together.

Don’t wait to apply - we review applications continuously and may close the position once the right candidate is found.

Posting text belongs to the employer. Removal requests: contact us.

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