Senior Data Engineer, Product Data & ML Insights

Zalando

Dublin

On-site

EUR 80,000 - 110,000

Full time

4 days ago
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Benefits offered by this job

Discounts on Zalando products
Volunteer days
Work from abroad
Vacation days
Ergonomic setup stipend
Health insurance
Pension matching
Life insurance
Income protection
Cycle to work
Tax saver tickets
Employee shares
Family services
Wellbeing options
Mental health support
Training platform

Job summary

Zalando is seeking a data engineer to join the Product Data Quality team in Dublin. You will design, build, deploy, and monitor cloud-based data processing architectures that synthesize insights from multiple data sources to enhance product information at scale.

The role involves working across data engineering, software development, and applied science with a modern tech stack including Databricks, Python, Airflow, Kubernetes, PostgreSQL, Elasticsearch and AWS.

Responsibilities

  • Lead the design, development, and deployment of the team's data pipelines, dashboards and other systems, demonstrating seasoned expertise.
  • Exhibit robust stakeholder management skills, fostering effective communication and collaboration with engineering peers, applied scientists, and product owners throughout the organisation.
  • Design, construct, and maintain resilient architectures adaptable to evolving product requirements.
  • Consistently deliver high-quality, testable, and dependable systems, fostering a culture of excellence through comprehensive reviews and mentorship.
  • Embrace agility by iteratively testing features with stakeholders while maintaining a holistic perspective on project goals.

Skills

Data pipelines
Cloud architectures
Stakeholder collaboration
Mentor teammates
Agile practices

Tools

Databricks
Airflow
Python
Kubernetes
PostgreSQL
Elasticsearch
AWS
Spark

Job description

Zalando is seeking a data engineer to join the Product Data Quality team in Dublin. You will design, build, deploy, and monitor cloud-based data processing architectures that synthesize insights from multiple data sources to enhance product information at scale.

The role involves working across data engineering, software development, and applied science with a modern tech stack including Databricks, Python, Airflow, Kubernetes, PostgreSQL, Elasticsearch and AWS.

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