Participate in design sessions with Enterprise and Hub Data Stewards, Engineering teams, Data Scientists, Product Managers, business and IT stakeholders, that result in design documentation for data processing, storage and delivery solutions.
Participate in evaluation of new technologies, Domino or Redshift, or new languages, like Go or React, including POCs.
Understand business capability needs and processes as they relate to IT solutions through partnering with Product Managers and business and functional IT stakeholders.
Implement data solutions according to design documentation using a variety of tools and programming languages, like Kafka, SQL and non-SQL databases, Scala, Go etc., and following team’s established processes and methodologies, like SCRUM or Kanban.
Participate in code reviews, retrospectives, functional and integration testing and other team activities focused on improving quality of delivery.
Collaborate with other data engineers and data stewards within the team and across data, technical platforms and product teams on aligning delivery dates and integration efforts.
Represent the team at various cross team meetings and events focused on design and planning, like Scrum of Scrums and Release Planning, sharing the results of team efforts, or brainstorming on process improvements.
Create and maintain design and code documentation in GitHub, Haystack, SharePoint and/or other repositories used by the team.
Bachelor’s degree in Computer Science, Software Engineering, or related field. 4 years of relevant experience is an acceptable substitute for the degree requirement.
Experience engineering data intensive software using streaming and/or resource based design principles
Demonstrated understanding of data architecture and modeling, including designing both logical and physical models for datasets
Exposure to writing queries and building data structures in relational databases such as (but not limited to) Postgres, MySQL, Oracle, etc.
Knowledge of at least one NoSQL database such as (but not limited to) Neo4j, Cassandra, etc.
Strong interpersonal skills and desire to work in a highly collaborative environment
Desired exposure to or experience with:
Machine learning or other data science practices
Agriculture, life sciences, bioinformatics, biochemistry, genetics, biology, or a related disciplines
Hybrid working style
Full time employment contract
Wide range of development opportunities
Attractive benefits package
Good working conditions and comfortable working environment