Data Engineer

About PA Consulting

Role overview

Working arrangement

• The role is hybrid, with work in the office or on client site a minimum of two days per week.
• Assignments may require up to five days per week on a client site.

Technology stack

• AWS is used for ETL pipelines, data warehouse and data lake design, development, and data movement.
• Relevant AWS services include EMR, Glue, Redshift, Kinesis, Lambda, and DynamoDB, or open-source equivalents.
• The role uses Java, Python, Scala, Spark, SQL, scripts, APIs, and SQL queries.

Role responsibilities

• Design and deploy production data pipelines from ingestion to consumption.
• Process structured and unstructured data within big data architectures.
• Integrate data from multiple sources through ingestion and curation functions on AWS.
• Work according to agile best practices with multiple teams and stakeholders.
• Solve technical problems with clients and contribute to internal projects.
• Design and build data solutions for the AWS cloud.

Essential requirements

• Experience designing and deploying production data pipelines within a big data architecture.
• Experience writing scripts, extracting data through APIs, and writing SQL queries.
• Experience processing large amounts of structured and unstructured data.
• Experience integrating multiple data sources on AWS using native or custom programming.
• Strong problem-solving and analytical thinking skills.
• Ability to collaborate with multiple stakeholders in a fast-paced environment.

Assessment process

• The process may include a recruiter call, two competency or technical interviews, and a final case study discussion.

Benefits and development

• The company offers technical and non-technical training, certification opportunities, private healthcare, annual leave, pension, performance-based bonus, share ownership, and community initiatives.