Engineering Manager - Data Engineering (all genders)

Job responsibilities

• You’ll lead the Data Engineering team in the Business Intelligence department, which consists of 5 data engineers. This team is responsible for creating, maintaining, and refining the core data pipeline tools, as well as supporting several end-user pipelines. Your team will assist the organization in addressing all its data needs and, simultaneously, enhance the data platform with new capabilities and refactoring.
• You will work closely with the data analytics and data science teams to enable them to leverage further the tools you have built, as well as develop and automate best practices for handling data on our platform.
• You will take on the responsibility to create an enabling DataMesh-based approach to support different teams in leveraging the data to create data-driven applications.
• Data Pipelines: Airflow + dbt-core, powered by Python.
• Data Storage & Querying: Redshift, Athena, DuckDB.
• Ingestion: Kafka, Airbyte, Fivetran.
• Automation & AI: Claude, Copilot, Codex.

Your role in this journey

This role is equal parts people leadership and hands‑on technical contribution. You won’t just manage — you’ll shape how the team works, roll up your sleeves when it counts, and set the technical standard by example. Here’s what that looks like day to day:

• Lead and grow your team. Coach 6 data engineers, create a culture of feedback and continuous learning, and recruit the people who will strengthen the team.
• Stay hands‑on. You’ll contribute directly to architecture decisions, code reviews, and complex technical challenges.
• Own the technical direction. Partner with Data Analysts, Data Scientists and stakeholders to set clear goals, prioritize the right work, and make sure the team builds things that actually matter.
• Drive engineering quality. Champion DataOps best practices — CI/CD for data pipelines, automated testing, monitoring, observability, and data quality standards across the board.
• Unblock and enable. Remove friction, resolve ambiguity, and make sure your engineers can do their best work without unnecessary overhead.
• Connect engineering to the business. Translate complex technical trade‑offs into plain language for non‑technical stakeholders and align solutions with real business needs.
• Push the stack forward. Evaluate new technologies with cost, velocity, and reliability in mind — and give your team the space to do the same.
• Embed AI into how your team works. Champion the use of LLM tools and AI agents to improve productivity and keep the team ahead of the curve.

Your backpack is filled with

• Extensive hands‑on experience as a Data Engineer, Software Developer, or in a closely related technical field, ideally in a fast‑paced startup or scale‑up environment.
• Deep experience with Lakehouse architectures on AWS and cloud‑native data platforms.
• Experience in building scalable batch and streaming pipeline architectures using tools like Airflow, dbt, Redshift, Athena, Spark, or similar.
• Strong command of Python and SQL.
• Solid understanding of DataOps principles: Infrastructure as Code (Terraform), CI/CD, automated testing, pipeline monitoring, and data quality management.
• Hands‑on experience with LLM tools and AI agents in a data engineering context.
• Experience with Data Governance frameworks and implementation is a plus.
• Strong technical leadership experience, including setting goals, defining priorities, designing systems, and guiding engineers through complex delivery.
• A passion and intuition for people management — you find meaning in helping others grow, you give feedback with care and directness, and you build team cultures based on trust. Formal people management experience is a plus, but not a hard requirement.
• Excellent communication skills with the ability to communicate technical decisions to engineers and non‑technical stakeholders.

Benefits

• Impact: Shape the future of travel with products used by millions of guests and thousands of hosts. At Holidu ideas become products, data drives decisions, and iteration fuels fast learning. Your work matters – and you’ll see the impact.
• Learning: Grow professionally in a culture that thrives on curiosity and feedback. You’ll learn from outstanding colleagues, collaborate across disciplines, and benefit from mentorship and personal learning budgets, with a strong focus on AI.
• Great People: Join a team of smart, motivated and international colleagues who challenge and support each other. We celebrate wins and keep our culture fun, ambitious and human. Our customers are guests and hosts — people we can all relate to — making work meaningful and energizing.
• Technology: Work in a modern tech environment. You’ll experience the pace of a scale‑up combined with the stability of a proven business model, enabling you to build, test, and improve continuously.
• Flexibility: Work a hybrid setup with 50% in‑office time for collaboration, and spend up to 8 weeks a year from other inspiring locations. You’ll stay connected through regular events and meet‑ups across our almost 30 offices.
• Perks on Top: We also offer travel benefits, gym discounts, and other perks to keep you energized — but what truly sets us apart is the chance to grow in a dynamic industry, alongside amazing people, while having fun along the way.

EEO Statement

We are committed to diversity in all aspects of our business. We encourage applications from all genders, all corners of the world and all individual backgrounds. You are welcome to submit your application without a photo and without stating your gender, date of birth, marital status, nationality or disability status (if applicable). If you require any special assistance when arranging interviews, office visits or the recruitment process in general, please contact the relevant HR person responsible for this job and we will do our best to accommodate your needs.