At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.
YOUR TASKS AND RESPONSIBILITIES
The primary responsibilities of this role, Data Engineer, are to:
- Lead and 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;
- Understand business capability needs and processes as they relate to IT solutions through partnering with Product Managers and business and functional IT stakeholders, and apply this knowledge to identifying business problems that could be solved;
- Evaluate new technologies, like Domino or Redshift, or new languages, like Go or React, including performing POCs and presenting results to others, with a goal of providing technical recommendations;
- Challenge the team to improve processes and methodologies, like SCRUM or Kanban, and/or initiate piloting new ones;
- 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., following team’s established processes and methodologies, like SCRUM or Kanban;
- Facilitate and participate in code reviews, retrospectives, functional and integration testing and other team activities focused on improving quality of delivery;
- Provide reliable estimates for short term projects and assist in large scale project estimation;
- Collaborate with other data engineers and stewards within the team and across data, technical platforms and product teams on aligning roadmaps, delivery dates and integration efforts;
- Mentor junior and aspiring Data Engineers on the team and across the data community;
- 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 another repositories used by the team;
- Deliver high-quality, creative and scalable technical solutions to problems related to team-owned product(s) and relevant platform(s);
- Work with engineers across the platform to ensure standards are being met;
- Spend significant time coaching and mentoring other engineers to drive team improvement and growth;
- Lead team conversations with product management, customers and other related groups.
WHO YOU ARE
Your success will be driven by your demonstration of our LIFE values. More specifically related to this position, Bayer seeks an incumbent who possesses the following:
- Bachelor’s degree in Computer Science, Software Engineering, or related field, with at least five years of professional software engineering experience or Master's degree with at least three years of relevant experience or PhD with one year relevant experience or at least nine years of relevant experience is an acceptable substitute for degree requirement;
- At least three years of experience engineering data intensive software using streaming and resource based design principles;
- At least two years of experience in least one NoSQL database, such as (but not limited to) Neo4j, Cassandra, etc.;
- At least three years of fluency in an object oriented or functional language such as Java, Scala, Go, etc.;
- Demonstrated experience with data architecture and modeling, including designing both logical and physical models for datasets;
- Proficiency in working with relational databases such as Postgres, MySQL, Oracle, etc.;
- Proven experience modeling large datasets in distributed databases such as (but not limited to) Apache Cassandra, Spanner, etc.;
- Strong interpersonal skills and desire to work in a highly collaborative environment;
- Familiarity with the relevant industry trends.
- Experience with Agriculture, life sciences, bioinformatics, biochemistry, genetics, biology, or a related disciplines;
- Experience with platform-as-a-Service software such as Cloud Foundry or Kubernetes;
- Experience with Stream processing, e.g. Kafka, Spark Streaming, Akka, etc.;
- Knowledge of machine learning or other data science practices.