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Data Engineer

ING Bank N.V.
AMSTERDAM ZUIDOOST, Netherlands
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
€1,083.0 - €2,083.0
Working hours
Regular working hours
Languages
English
Job source
indeed.com

Tech stack

Java (Programming Language) Airflow Amazon Web Services Automation of Tests Microsoft Azure BigQuery Continuous Integration Data Governance Data Flow Control Python (Programming Language) Apache Maven Standard Sql
+9 more
Unstructured Data Google Cloud Apache Spark Git Apache Flink Apache Kafka Terraform Looker Analytics Apache Beam

Job description

  • Work with cutting-edge cloud technologies (GCP, BigQuery, Dataflow, Terraform).
  • Be part of an agile, international team focused on innovation.
  • Enjoy a culture of continuous learning and career growth.

What You’ll Do

  • Design, develop, and optimize cloud-based data pipelines.
  • Automate testing and ensure security, stability, and performance.
  • Work with structured and unstructured data across cloud and on-prem environments.
  • Contribute to architecture decisions and best practices.
  • Collaborate with teams to deliver high-quality, efficient solutions.

Requirements

Do you have experience in Terraform?, * You have strong SQL and database expertise.

  • You are experienced with Python or Java.
  • You have experience with GCP (BigQuery, Dataflow, Cloud Composer) or other public cloud providers equivalents (AWS, Azure).
  • You know CI/CD tools (Azure DevOps, Git, Maven), Automated Testing, and Infrastructure as Code (e.g., Terraform).
  • You are analytical and proactive.
  • Know English on advanced level.

Nice-to-Have:

  • DBT, Looker, data governance.
  • Experience with Apache Beam, Spark, Flink, or Kafka.

Ready to Make an Impact?

Apply for this position

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

Apply on indeed.com

Good distractions

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

Moments

Explore playlists

2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · WWC Europe 2026

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

3:27 min

Explaining query execution overhead and caching limitations in BigQuery

Adnan Rahic · JS Congress

4:59 min

Bringing DevOps practices to data transformation with DBT

Matthias Niehoff Matthias Niehoff · WWC 2024

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

3:05 min

Audience questions on AI agents and pipeline vectorization

Joy Joy · WWC 2024

Videos

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From Messy Queries to Scalable Systems - How Data Engineering actually works thumbnail
31:15
WWC Europe 2026 • about 1 month ago

From Messy Queries to Scalable Systems - How Data Engineering actually works

Sandhya Menon

Data Science in Retail thumbnail
58:21
LIVE • about 3 years ago

Data Science in Retail

Julian Joseph

How a Small Team Shrank a Microsoft Monorepo by 94% thumbnail
33:23
Coffee With Developers • almost 2 years ago

How a Small Team Shrank a Microsoft Monorepo by 94%

Jonathan Creamer

Enjoying SQL data pipelines with dbt thumbnail
26:53
WWC 2023 • almost 3 years ago

Enjoying SQL data pipelines with dbt

Matthias Niehoff

Data Governance in the Era of AI thumbnail
20:04
WWC 2025 • 12 months ago

Data Governance in the Era of AI

Kateřina Ščavnická

Making Data Warehouses fast. A developer's story. thumbnail
42:16
JS Congress • over 4 years ago

Making Data Warehouses fast. A developer's story.

Adnan Rahic

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