Data Engineer (Amsterdam)

Role: Data Engineer
Complete fluency in Dutch is required for this role in order to communicate with our Dutch Stakeholders.
AND Introduction:
At AND, we accelerate the development of digital capabilities. In practice, that means helping ambitious leaders and organisations build the teams, products, processes and even operational structures they need to close the digital skills gap within their organisation today, so that they thrive tomorrow.
Clients rely on our experience, agility and craft skills across tech and business strategy, software development, data engineering and agentic AI to address some of the toughest challenges facing their businesses.
We bring aboard thinkers, tinkerers, passionate craftspeople and inspiring technologists to help us solve these challenges. Together, we’re united by a sense of pragmatism, purpose and a deeply-held belief that digital products and technology alone won’t transform a business or save the world: it’s the people that count.
About You:
As a Data Engineer, you will spend your time helping clients achieve their data engineering needs. Primarily the development, deployment and maintenance of data products in a fast moving, Agile environment.
You’ll also make a real impact by taking an active role in the team’s Agile Development practices, technical decision making and development, generating value and continuously striving to improve the quality and reliability of our data and processes.
You will spend the majority of your time helping deliver client data engineering opportunities and supporting the growth of our junior-mid level technologists; both within AND and for our clients.
Key Skills:
Expertise
Required
Strong expertise in Python and PySpark/Spark for building scalable data pipelines
Strong knowledge of SQL for querying structured data and interacting with databases, including PostgreSQL
Strong understanding of data modelling, ETL/ELT processes and data governance
Experience with data warehousing concepts and delivering analytical insights to internal stakeholders
Deep expertise in at least one major cloud platform (AWS, Azure, or GCP)
Experience with Apache Airflow for workflow orchestration and pipeline scheduling
Hands-on experience with AWS services, particularly Glue and Redshift
Strongly Desired
Experience with Apache Kafka or similar streaming technologies
Experience with Delta Lake/Delta Table, Lakehouse or Medallion Architecture (Bronze/Silver/Gold)
Deep expertise in modern data platforms such as Databricks or Snowflake
Experience with data migration, including familiarity with tools such as AWS DMS
Consulting or client-facing experience, translating business requirements into data solutions
Nice to Have
Familiarity with Data Vault 2.0 and Star Schema design
Infrastructure as Code experience (Terraform or AWS CloudFormation)
Familiarity with enterprise tooling such as Informatica (ETL, Data Governance, Data Quality) or Data Mesh enablers
Dataiku experience
Responsibilities
Stack Migration: Migrating the existing data processing stack (PostgreSQL/Jenkins/Python) to a modern cloud-based stack (AWS/Airflow/Redshift/Python/PySpark/Spark), ensuring continuity and data integrity throughout the transition
Design and Build Scalable ETL Pipelines: Build and optimise ETL/ELT data pipelines, focusing on performance, scalability, and data integrity. Ensure pipelines integrate smoothly within the broader data ecosystem and internal Data Warehouse
Maintain and Develop Data Pipelines: Support and maintain existing pipelines while building new ones to meet evolving business needs and stakeholder requirements
Streaming & Integration: Develop and maintain both batch and real-time data processing pipelines from multiple data sources, with awareness of streaming solutions such as Kafka/Confluent
Support DevOps Practices: Contribute to CI/CD processes for testing, building, and deploying data pipelines, including supporting the transition away from Jenkins-based workflows
Performance Optimisation: Tune pipeline performance for both batch and real-time data processing. Troubleshoot and debug complex issues in distributed and cloud-native environments
Collaboration and Mentorship: Partner with internal teams and engineers to ensure seamless data integration. Provide technical leadership, mentorship and guidance to junior engineers, fostering best practices
Joining AND:
From the work we deliver, to the way we serve and support our people, we work hard to ensure that there’s nowhere quite like AND. But joining a company is a two-way street: the fit has to work on both sides. So before you apply, here’s three key things to understand about us:
We’re built for people - like, real humans. Not ‘resources’ or ‘staff’. That means happiness and wellbeing really do matter to us, and we hate unnecessary hierarchy and bureaucracy.
There’s no well-trodden path ahead: AND is growing fast and forging a new trail. That’s exciting, and gives us all the autonomy and opportunity we love - but bear in mind it also demands focus, patience and resilience.
Diversity is a priority. After all, to build great products that a wide variety of different people love to use, we need a wide variety of people to help us build them. So diversity is more than a policy or a word: it’s business critical for us.