Senior Data Engineer
@ Barclays

Glasgow, Scotland, United Kingdom
£120,000
On Site
Posted 24 days ago

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XXXXXXXXX XXXXXXXXXXX XXXXXX****** @barclays.com
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Job Details

Role Overview

Join Barclays as a Senior Data Engineer, responsible for designing, building, and optimizing data pipelines and frameworks across AWS, Azure, and on-premises environments. You will build and maintain systems that collect, store, process, and analyse data, ensuring high-quality, secure and scalable data solutions.

Main Responsibilities

  • Design, build and maintain robust ETL/ELT data pipelines.
  • Develop data warehouses and lakes adhering to security measures.
  • Create processing and analysis algorithms for complex data volumes.
  • Collaborate with data scientists to deploy machine learning models.
  • Lead projects and teams, advising on risk management and policy development.

Technical Requirements

  • Expertise in Apache Airflow, dbt, PySpark, Python, AWS Glue, Lambda, Athena, Snowflake, and Databricks.
  • Experience with data quality frameworks and metadata governance tools.
  • Hands-on cloud-native and on-premises data engineering skills.
  • Familiarity with DevOps practices and CI/CD for data pipelines.
  • Understanding of observability and cost optimization in data environments.

Leadership & Collaboration

This role involves advising on strategic decision making, mentoring team members, and collaborating across business divisions. Barclays values respectful, honest, and team-oriented approaches aligned with its core values and mindset.

Key skills/competency

  • Data Pipelines
  • ETL/ELT
  • Cloud Engineering
  • Data Warehousing
  • Machine Learning Collaboration
  • DevOps
  • Governance
  • Security
  • Risk Management
  • Team Leadership
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How to Get Hired at Barclays

🎯 Tips for Getting Hired

  • Customize your resume: Highlight relevant data pipeline and cloud skills.
  • Research Barclays culture: Study values, recent initiatives, and tech projects.
  • Emphasize leadership: Showcase team management and strategy experience.
  • Prepare technical examples: Demonstrate success with ETL and data governance.

📝 Interview Preparation Advice

Technical Preparation

Review Apache Airflow and dbt documentation.
Practice coding in Python and PySpark.
Study cloud data storage and compute fundamentals.
Set up small projects using AWS Glue and Lambda.

Behavioral Questions

Describe team leadership challenges faced.
Explain cross-functional collaboration experiences.
Share a problem-solving success story.
Discuss conflict resolution in teamwork.

Frequently Asked Questions