Lead Data Engineer- Databricks

Marktplaats BV
Amsterdam, Netherlands
27 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Languages
English
Job source

Tech stack

Artificial Intelligence Airflow Amazon Web Services Data Validation Information Engineering Data Governance Database Applications Python (Programming Language) Simple Data Format Software Engineering SQL Databases Parquet
+10 more
Apache Spark Containerization Data Lakes Pyspark Kubernetes Data Management Machine Learning Operations Terraform Docker Databricks

Requirements

For this position the ideal candidate has 10+ years of hands-on experience in Software Development/Data Engineering. Prior experience building and operating data platforms is a plus.

  • Experience with Databricks (Lakehouse, ML/MosaicAI, Unity Catalog, MLflow, Mosaic AI, model serving etc).
  • Proven experience on building cloud native data intensive applications (both real time and batch based). AWS experience is preferred.
  • Strong background in Data Engineering to support other Data Engineers, Back Enders and Data Scientists in building data products and services.
  • Hands-on experience of building and maintaining Spark applications. Python and PySpark(Scala Spark is a plus)
  • Experienced in AWS Cloud usage and data management (automation, data governance, cost optimisation, delivering reliable & scalable data solutions)
  • Ensure data quality, schema governance and monitoring across pipelines.
  • Experience with orchestrators such as Airflow, Databricks workflows.
  • Solid experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
  • Fundamental understanding of various Parquet, Delta Lake and other OTFs file formats.
  • Proficiency on an IaC tool such as Terraform or Terragrunt.
  • Data validation/analysis skills & proficiency in SQL is considered as a foundational skill.
  • Collaborate in a small, fast moving team with high levels of autonomy and impact.
  • Strong written and verbal English communication skill and proficient in communicating with non-technical stakeholders.

Benefits & conditions

Life at Marktplaats comes with its perks! Our colleagues enjoy the following benefits:

  • Attractive Base Salary

  • Participation in our Short-Term Incentive Plan (Annual Bonus)

  • ️ Employee Assistance Program: 24/7 support for you and your family

  • Collaborative Culture: “Win together, lose together” is one of our key behaviours. You’ll be part of a supportive, growth-minded environment.

Ask our recruiters to tell you more!

Equal Opportunity Statement

About the company

In the Marktplaats data and analytics teams, data is at the heart of everything we do. As a Data Engineer of the Data Platform team at Marktplaats you will be relied on to independently develop and deliver high-quality features for our new Data/ML Platform, refactor and translate our data products and finish various tasks to a high standard. You will be the cornerstone of the platform’s reliability, scalability and performance, working hands on with batch and streaming data pipelines, storage solutions and APIs that serve complex analytical and ML workloads.The role encompasses ownership of the self-serve data platform, including data collection, lake management, orchestration, processing, and distribution.

Success in this role requires a high level of technical proficiency in modern data technologies and cloud-based environments, Databricks, AWS, Spark, Python, Kafka, Airflow, and deep expertise in data management and governance frameworks.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.adzuna.nl

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon ¡ WWC Europe 2026

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Career evolution in data engineering and AI platforms

Maria Apazoglou ¡ Coffee With Developers

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Harnessing Spark with Python using PySpark and Py4J

Ayon Roy ¡ LIVE

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz ¡ WWC 2025

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Scaling machine learning pipelines from prototypes to petabytes

Julian Joseph ¡ LIVE

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Audience questions on AI agents and pipeline vectorization

Joy Joy ¡ WWC 2024

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