Senior Data Engineer (Senior Associate)

Archer

United States

On-site

USD 140,000 - 190,000

Full time

8 hours ago
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Job summary

Archer, collaborating with Kainos, seeks a Senior Data Engineer to design and develop scalable data processing systems. You will contribute to big data solutions, lead development, and guide teams in production-ready data pipelines.

Ideal candidates have strong Java/Scala/Python skills, expertise in data platforms, and a passion for AI technologies. Expect collaboration with cross-functional teams in a fast-paced Agile environment.

Qualifications

  • Strong software development experience in Java, Scala, or Python.
  • Experience with data-processing platforms from AWS, Azure, GCP, Databricks.
  • Developed substantial components for large-scale data processing and production deployment.
  • Proficient in SQL and analytical SQL extensions.
  • Solid understanding of ETL/ELT patterns for data processing.

Responsibilities

  • Develop data processing software for Big Data deployments from design to test and deployment.
  • Collaborate with Architects and Lead Engineers to support non-functional requirements.
  • Mentor and coach team members while upholding code quality and maintainability.
  • Coordinate with operations for production readiness and monitoring.
  • Estimate effort and implications of user stories for stakeholders.
  • Provide guidance and expertise on data best practices.

Skills

Java
Scala
Python
SQL
ETL/ELT
CI/CD
AI
Distributed data processing

Tools

AWS
Azure
GCP
Databricks

Job description

Archer is collaborating with Kainos to connect them with exceptional professionals for this role.

As a Senior Data Engineer (Senior Associate) at Kainos, you will be responsible or designing and developing data processing and data persistence software components for solutions which handle data at scale. Working in agile teams, Senior Data Engineers provide strong development leadership and take responsibility for significant technical components of data systems. You will work within a multi-skilled agile team to design and develop large-scale data processing software to meet user needs in demanding production environments.

Your Responsibilities Will Include
  • Working to develop data processing software primarily for deployment in Big Data technologies. The role encompasses the full software lifecycle including design, code, test and defect resolution.
  • Working with Architects and Lead Engineers to ensure the software supports non-functional needs.
  • Collaborating with colleagues to resolve implementation challenges and ensure code quality and maintainability remains high. Leads by example in code quality.
  • Working with operations teams to ensure operational readiness
  • Advising customers and managers on the estimated effort and technical implications of user stories and user journeys.
  • Coaching and mentoring team members.
Minimum (essential) Requirements
  • Strong software development experience in one of Java, Scala, or Python
  • Software development experience with data-processing platforms from vendors such as AWS, Azure, GCP, Databricks.
  • Experience of developing substantial components for large-scale data processing solutions and deploying into a production environment
  • Proficient in SQL and SQL extensions for analytical queries
  • Solid understanding of ETL/ELT data processing pipelines and design patterns
  • Aware of key features and pitfalls of distributed data processing frameworks, data stores and data serialisation formats
  • Able to write quality, testable code and has experience of automated testing
  • Experience with Continuous Integration and Continuous Deployment techniques
  • A Keen interest in AI Technologies
Desirable Requirements
  • Experience of performance tuning
  • Experience of data visualisation and complex data transformations
  • Experience with steaming and event-processing architectures including technologies such as Kafka and change-data-capture (CDC) products
  • Expertise in continuous improvement and sharing input on data best practice
  • Practical experience with AI technologies, tools, processes and delivery
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