Staff Data Platform Engineer

Harnham; Amsterdam; On-site; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Competitive salary

Modern data & ML technologies

Autonomy & ownership

Job summary

Harnham is seeking a Senior Data Engineer to shape a modern data platform powering analytics and ML at scale. You will build and maintain scalable data pipelines, enabling data-driven decisions across the business.

Working with Databricks, AWS and modern data storage formats, you will collaborate with data scientists and engineers to deliver robust data products and services. You’ll own reliability and governance while advancing automation.

Qualifications

• Extensive experience in data engineering and distributed data systems.
• Strong Python, PySpark, Spark and SQL capabilities.
• Experience with cloud-native data applications on AWS.
• Familiarity with Delta Lake and Parquet formats.
• Knowledge of data governance, quality frameworks and monitoring.

Responsibilities

• Build and enhance a self-service data platform for analytics and ML workloads.
• Design scalable batch and real-time data pipelines.
• Improve platform reliability, performance and efficiency.
• Develop cloud-native data solutions at scale.
• Implement data quality, governance, monitoring and schema management.
• Collaborate with Data Engineers, Software Engineers and Data Scientists.
• Support data collection, processing, storage and distribution.
• Contribute to infrastructure automation and platform engineering.

Skills

Data Engineering

Python

PySpark

SQL

Spark

Cloud

Streaming

Kafka

Airflow

Docker

Kubernetes

Terraform

Delta Lake

Parquet

Tools

Databricks

AWS

Databricks Lakehouse

MLflow

Unity Catalog

Mosaic AI

Model serving

Job description

This is an opportunity to play a key role in shaping a modern data platform that powers analytics and machine learning at scale. You'll work on complex technical challenges, influence platform strategy, and help build the foundations that enable data-driven decision making across the business.

The Company

They are a technology-focused organisation where data plays a central role in driving innovation and business performance. The company is investing heavily in its cloud-based data and machine learning ecosystem, creating an environment where engineers can have a meaningful impact. You will join a collaborative team that values technical excellence, ownership, and continuous improvement.

The Role

• Build, develop, and enhance a self-service data platform supporting analytics and machine learning workloads.
• Design and maintain scalable batch and real-time data pipelines.
• Improve platform reliability, performance, and operational efficiency.
• Develop cloud-native data solutions and infrastructure at scale.
• Implement data quality, governance, monitoring, and schema management best practices.
• Partner with Data Engineers, Software Engineers, and Data Scientists to enable data products and services.
• Support data collection, orchestration, processing, storage, and distribution capabilities across the platform.
• Contribute to infrastructure automation and platform engineering initiatives.

Your Skills & Experience

• Strong commercial experience in Data Engineering and distributed data systems.
• Expertise with Databricks, including Lakehouse architecture, Unity Catalog, MLflow, Mosaic AI, and model serving capabilities.
• Experience building cloud-native data-intensive applications within AWS environments.
• Strong Python, PySpark, Spark, and SQL skills.
• Experience working with batch and streaming data architectures.
• Knowledge of Kafka, Airflow, Databricks Workflows, or similar orchestration technologies.
• Experience with data governance, data quality frameworks, and platform monitoring.
• Understanding of Docker, Kubernetes, Terraform, or comparable infrastructure technologies.
• Familiarity with Delta Lake, Parquet, and modern data storage formats.
• Excellent stakeholder engagement and communication skills.

What They Offer

• Competitive salary and benefits package.
• The opportunity to work with modern data and machine learning technologies.
• High levels of ownership and autonomy within a collaborative engineering environment.
• Exposure to large-scale data, analytics, and AI initiatives.
• Ongoing professional development and clear opportunities for career progression.