Data Engineering Manager

Based in any location:
France, Germany, the Netherlands, or the United Kingdom

Angi is looking for an Engineering Manager with strong leadership, technical depth, and delivery experience to help shape the future of our global data platform. You’ll lead the Data Products & Enablement (DPE) team within the Data Platform Products focus area under the Technical Foundations Zone – the group responsible for building, scaling, and maintaining the foundational data products, shared models, and enablement layers that power analytics, experimentation, and marketing technology across Angi.

As an Engineering Manager, you will lead a multidisciplinary team of data and software engineers who build the data pipelines, shared models, and integration platforms that enable data‑driven decisions and product experiences across the company. You’ll balance people leadership with technical depth – driving delivery, coaching high‑performing engineers, and ensuring the reliability and scalability of Angi’s core data assets.

• Lead and mentor a high‑performing team of data and software engineers, driving impact through coaching, feedback, and performance management.
• Deliver scalable, high‑quality data products, shared models, and enablement platforms that serve analytics, marketing, and product teams across Angi.
• Design, evolve, and standardize data pipelines and transformations using modern tools such as dbt, Airflow, and Snowflake.
• Drive major data migrations and modernization initiatives from legacy systems to unified, cloud‑based data platforms.
• Collaborate closely with Product, Analytics, and Marketing Technology teams to build and maintain reliable data flows for key business domains (e.g., event tracking, user funnels, marketing conversions, CRM integrations).
• Oversee event tracking and analytics integrations using technologies such as Confluent/Kafka, Snowplow, Segment, or Adobe Analytics.
• Enable downstream systems and teams by designing robust data contracts, APIs, and reverse ETL solutions.
• Contribute to platform reliability and efficiency, leveraging containerization (Docker) and infrastructure‑as‑code tools (Terraform, etc.) to streamline deployments and data operations.
• Foster a strong engineering culture, balancing technical rigor, experimentation, and delivery focus while supporting your engineers’ professional growth.
• Leverages AI tools (e.g., Copilot, Cursor, Claude Code) to improve coding speed and debug faster.

• 8+ years of professional experience in data engineering or software engineering, with exposure across data, analytics, and platform domains.
• 2+ years of experience managing engineering teams, including performance management, promotions, and building high‑performing teams.
• Experienced in managing both data engineers and software engineers, providing guidance while maintaining a balance between technical depth and leadership.
• Proven experience designing and operating large‑scale, cloud‑based data platforms and systems – not limited to small datasets or companies.
• Hands‑on experience with SQL and Python, and the ability to engage technically in design reviews and solution discussions.
• Strong experience with the modern data stack, including dbt (advanced proficiency), Airflow (or similar orchestration tools), Spark, Snowflake, Redshift, Trino, Fivetran and ETL/ELT frameworks.
• Familiar with event tracking and analytics platforms such as Confluent/Kafka, Snowplow, Segment, or Adobe Analytics.
• Working knowledge of containerization (Docker or similar) and infrastructure automation (Terraform or similar).
• Exposure to marketing and conversion APIs (Google Ads, Microsoft Ads, or equivalent) and CRM tools (Salesforce, Iterable, or similar).
• Excellent communication skills, capable of partnering with Product, Marketing, and Analytics stakeholders to deliver data solutions that drive business value.
• Experience implementing or contributing to data mesh architectures.
• Programming experience in Java, Kotlin, or PHP.
• Familiarity with Kubernetes, infrastructure engineering, and Terraform.
• Experience with Reverse ETL tools (e.g., Census, Hightouch).
• Experience with BI tools (Looker, Tableau, or…