Engineering Manager - Data & ML Platform (m/f/d)

Flink; Berlin; Vor Ort; EUR 85.000 - 120.000; Vollzeit

Zusammenfassung

A leading quick commerce company in Berlin is seeking an Engineering Manager for their Data & ML Platform. This role requires expertise in leading engineering teams, building scalable data infrastructures, and enhancing machine learning capabilities. Candidates should have experience with data pipeline operations and strong skills in cloud infrastructure. The company values diversity and aims to foster a culture of continuous improvement and data-driven decision-making.

Qualifikationen

• Demonstrated leadership with high-performing data teams.
• Experience operating data platforms at scale.
• Strong foundation in distributed systems and data architecture.

Aufgaben

• Lead and grow engineering teams for data infrastructure.
• Drive product and business impact through collaboration.
• Own critical data systems, ensuring reliability and quality.

Kenntnisse

People leadership

Data platform operations

Distributed systems

Cloud infrastructure

Communication skills

Tools

BigQuery

Apache Airflow

Kubernetes

GCP

Terraform

Jobbeschreibung

Engineering Manager - Data & ML Platform (m/f/d)

Flink is the leading quick commerce player in Europe. We are on a mission to give people back time: You can order your groceries through our app and we deliver to your doorstep in minutes. We carry 3,000 products with a focus on the leading brands in each category. We aim for sustainability by making deliveries on electric bikes and utilizing recyclable packaging.

Flink launched in February 2021 and already operates in more than 90 cities in Germany, and the Netherlands. The business generated more than EUR 400m in revenues in 2024 and is operationally profitable. Flink is backed by the world’s most renowned tech investors, including Prosus, Mubadala, and Bond, and strategic investors like Doordash and REWE. We take great pride in being an inclusive employer that offers equal opportunities, and we celebrate the diversity and multiculturalism of our team. We\'re growing fast and always pushing ourselves to do better - we play for #1.

To power our next phase of growth, we are looking for an exceptional Engineering Manager (m/f/d) to lead and scale our core Data & ML Platform team. This is a critical leadership role where you will build the foundational systems that enable the entire organization to make smarter, faster decisions.

As the Engineering Manager for Data & ML Platform (m/f/d), you\'ll play a vital role in Flink\'s success. You\'ll lead a cross-functional engineering team that builds and maintains the data infrastructure and machine learning platform powering data-driven decision making across Flink, from data pipelines and warehousing to ML model training, deployment, and monitoring. You\'ll work closely with data scientists, platform engineers, analysts, and product teams to enable self-service Data access and accelerate ML adoption company-wide.

• Lead & Grow Engineers: Build high-trust environments where engineers thrive, with accountability for hiring, onboarding, and performance management while ensuring each team member has a clear career path and receives regular, actionable feedback. Help your team get 1% better every day.
• Drive Product & Business Impact: Partner with Data Science and Analytics to shape initiatives that unlock fast and self-service Data Platform, power ML models, and enable teams across Flink to make faster, better decisions.
• Own Critical Systems: Lead teams managing data pipelines, data warehouse architecture, ML training infrastructure, feature stores, and model serving systems that form the foundation of Flink\'s data-driven capabilities.
• Guide Technical Direction: Shape the technology strategy for Data & ML Platform, lead the architectural decisions and RFC discussions, and champion reliability, data quality, and pragmatic engineering, with customers as our first priority.
• Champion Reliability & Observability: Set operational excellence standards through SLIs/SLOs, monitoring, and incident response for critical data systems. Lead blameless postmortems, driving continuous improvement.
• Reduce Toil & Accelerate Delivery: Invest in automating pipelines, reducing overhead by being ahead, and building self-service capabilities that empower data consumers and maintain sustainable velocity.
• Foster Strong Engineering Culture: Create an environment where the best idea wins. Embody our values by supporting team members, celebrating achievements, and never letting another Flinker fail.
• Cultivate a Data-First Mindset: Ensure the team prioritizes data quality, privacy compliance (GDPR), and responsible ML practices to protect customer trust.
• Partner Across Flink: Collaborate with peer Engineering Managers to share learnings and improve engineering practices, driving data literacy organization-wide.

We're looking for a leader who is passionate about building scalable data infrastructure, ML platforms, and even stronger teams. You thrive in a fast-paced environment and are excited by the challenge of enabling data-driven decision-making at scale.

Qualifications

• Demonstrated people leadership with a track record of building high-performing data or platform engineering teams
• Direct experience operating data platforms at scale, including data pipelines, warehousing (e.g., BigQuery), and orchestration tools, preferably Apache Airflow
• Strong technical foundation in distributed systems, data engineering, and platform architecture
• Proven experience with cloud infrastructure, container orchestration, and Infrastructure as Code (e.g., Kubernetes, GCP, Terraform)
• Experience with ML infrastructure components such as feature stores (e.g. Feast), model registries, and ML serving systems
• Experience running high-reliability data services with observability and data quality practices
• Clear communication, translating technical challenges into a business context

Nice to have

• Experience with AI tools like Claude Code for development acceleration
• Hands-on experience with ML serving frameworks and MLOps tools (e.g., Kserve, MLflow)
• Background in real-time streaming systems (e.g., Google Pub/Sub, Dataflow)
• Experience with data governance, privacy regulations (GDPR), and data cataloging
• Experience with dbt Cloud or dbt Core for data transformation

It is our commitment that every applicant will be evaluated according to their skills regardless of age, gender identity, ethnicity, sexual orientation, disability status, or religion.

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