Senior Data & ML Engineering Lead

Catawiki; Amsterdam; Hybrid; EUR 120,000 - 180,000; Full time

Benefits offered by this job

Catavoucher on joining

Birthday Catavoucher

Extra day off for personal pursuits

Job summary

Catawiki in Amsterdam is seeking a Senior Manager – Data Engineering & Machine Learning to lead eight data engineers and ML specialists across Amsterdam and Lisbon, set technical direction and advance data foundations and production machine learning.

You will partner with Product, Engineering, Analytics and business stakeholders to set priorities, connect the team’s work to outcomes, and drive modernization, feature store adoption, observability and cost controls.

Qualifications

• Deep experience in Data Engineering or ML Engineering with breadth across the other discipline.
• Proven track record leading experienced engineers or ML specialists.
• Ability to connect technical work to business goals and priorities.

Responsibilities

• Lead the team through platform modernisation and production ML work.
• Set direction, coach specialists and establish clear ownership across Data Eng and ML.
• Improve data pipelines, integrations and infrastructure used for analysis, reporting and ML.
• Advance marketplace models such as recommendations and bidder-risk use cases, tying outcomes to product impact.
• Collaborate with Product, Engineering, Analytics and stakeholders to prioritise high-value problems.

Skills

Data Engineering

Machine Learning Engineering

People leadership

Architecture and systems thinking

Production ML

Cloud platforms (GCP, Vertex AI, BigQ,

Kafka / data streaming

Tools

BigQuery

Vertex AI

Kubernetes

Kafka

Job description

Catawiki in Amsterdam is seeking a Senior Manager – Data Engineering & Machine Learning to lead eight data engineers and ML specialists across Amsterdam and Lisbon, set technical direction and advance data foundations and production machine learning.

You will partner with Product, Engineering, Analytics and business stakeholders to set priorities, connect the team’s work to outcomes, and drive modernization, feature store adoption, observability and cost controls.