FanDuel

Technology

PrincipalDataEngineer

€360–540k ~AI est. Cluj-Napoca, Romania Remote Friendly
The Brief

“Principal Data Engineer at FanDuel. Skills: Data Engineering, Data Architecture, Data Pipelines. Design data solutions. Build data solutions”

What You'll Achieve.

Power analytics; Power machine learning; Power business operations; Drive business outcomes

Industry & Context.

Technology
Problems you'll solve

Problem solving

What They're Looking For.

Must Have

5+ years data engineering, Experience with Spark, Experience with dbt, Experience with ETL/ELT pipelines, Experience with batch and streaming data pipelines, Experience with large-scale datasets, Experience with database performance analysis, Unit testing knowledge, Experience with CI/CD tools, Problem-solving skills, Ability to work independently

Nice to Have

Experience working in Agile environments, Experience supporting analytics, Experience supporting machine learning workflows, Familiarity with data governance, Familiarity with data privacy, Familiarity with compliance frameworks, Experience working in a product-led organization, Experience working in a customer-centric organization, Familiarity with infrastructure-as-code, Familiarity with DevOps practices

What You'll Do.

Design data solutions

Implement data pipelines

Implement data architectures

Define data engineering standards

Define data product design standards

Define pipeline orchestration standards

Translate requirements into data solutions

Enforce engineering best practices

Contribute to data platform evolution

Lead technical design reviews

Identify architectural bottlenecks

Resolve architectural bottlenecks

Propose platform improvements

Improve data observability

Improve system reliability

Act as technical liaison

Evaluate new technologies

Onboard new technologies

Design ETL/ELT pipelines

Develop ETL/ELT pipelines

Maintain ETL/ELT pipelines

Work with complex datasets

Ensure data accessibility

Develop batch pipelines

Develop streaming pipelines

Develop data platforms

Build reusable data models

Build reusable data assets

Understand business needs

Translate needs into solutions

Ensure data consistency

Promote software engineering best practices

Participate in technical design discussions

Participate in architecture reviews

How You'll Work.

Team & Collaboration

Cross-functional stakeholders; Data engineering teams; Analytics teams; Data science teams; Engineering teams; Product teams; Analytics teams

Communication Scope

Explain technical concepts

Free ATS check

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