Senior ML Data Engineer: Real-Time Feature Pipelines

Cph Ai Hub; København; Hybrid; DKK 1,100,000 - 1,500,000; Full time

Benefits offered by this job

Birthday leave

30 days vacation

Pension and insurance

Weekly lunch program

Unlimited snacks

Job summary

GoWish is seeking a systems-minded Senior ML Data Engineer to own offline-to-online feature infrastructure powering real-time recommendation and search engines. You will build low-latency data syncs and feature-serving layers bridging warehouses with operational stores, caches, and Feature Stores.

Responsibilities include building resilient pipelines, orchestrations with Airflow and dbt, and IaC with Terraform and Docker to ensure sub-second queries and SLAs.

Qualifications

• 4+ years of experience in data engineering or ML data platforms.
• Experience moving batch features from warehouses to low-latency online stores.
• Hands-on IaC using Terraform and Docker with CI/CD.
• Strong SQL for OLAP and OLTP, performance tuning and schema optimization.

Responsibilities

• Build and operate offline-to-online feature pipelines for real-time models.
• Design Airflow DAGs and dbt transformations for low-latency data ingestion.
• Provision and automate cloud data infra with Terraform, Docker, and CI/CD.
• Collaborate with Data Scientists and Backend Engineers on feature contracts.

Skills

Operational Data Pipelines

IaC

Pipeline Orchestration

SQL Performance Tuning

Tools

Terraform

Docker

Airflow

dbt

BigQuery

Redis

Flink

Kafka

Job description

GoWish is seeking a systems-minded Senior ML Data Engineer to own offline-to-online feature infrastructure powering real-time recommendation and search engines. You will build low-latency data syncs and feature-serving layers bridging warehouses with operational stores, caches, and Feature Stores.

Responsibilities include building resilient pipelines, orchestrations with Airflow and dbt, and IaC with Terraform and Docker to ensure sub-second queries and SLAs.