Data Engineer @ PA Consulting
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Company Overview
At PA Consulting, we believe in the power of ingenuity to build a positive human future. Our diverse teams of strategists, innovators, designers, consultants, digital experts, scientists, engineers, and technologists operate globally from offices across the UK, Ireland, US, Nordics, and Netherlands.
PA Consulting is dedicated to driving transformation by combining innovative thinking with breakthrough technologies to generate enduring results.
Role Overview
The Data Engineer at PA Consulting is a multi-year, project-based opportunity focused on building and growing a clinical data registry platform. You will design, build, and maintain data infrastructure to harness data's power in advancing healthcare and improving patient outcomes.
Your Day-to-Day
- Designing and constructing Big Data Lakes and Data Warehouses.
- Building fully automated ETL/ELT pipelines for diverse datasets.
- Optimizing, managing and expanding data infrastructure.
- Developing dynamic, metadata driven pipelines and analyses.
- Working within agile and DevOps environments with cloud technologies.
Qualifications & Skills
Minimum qualifications include 2-4 years industry experience, advanced SQL and Python skills, and expertise in designing and constructing large-scale data systems. Cloud experience (Azure, AWS, or GCP) is required, with Spark/PySpark being highly preferable.
Work Environment & Benefits
This is a hybrid role requiring a minimum of 2 days per week onsite. Enjoy comprehensive benefits including medical, dental, vision, life insurance, paid vacation, 401(k) with profit sharing, and additional perks to support your well-being.
Key skills/competency
Data Engineering, SQL, Python, ETL, Cloud, Big Data, Data Warehousing, Agile, DevOps, Spark
How to Get Hired at PA Consulting
🎯 Tips for Getting Hired
- Customize your resume: Emphasize SQL, Python, and ETL skills.
- Research PA Consulting: Align with their innovation and technology culture.
- Highlight cloud expertise: Clearly list Azure, AWS, GCP credentials.
- Practice technical interviews: Focus on data architectures and pipelines.