Staff Data Eng

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Staff 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 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 defining business problems that need to be solved;
• Initiate and lead evaluation of 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;
• Help the team establish and improve processes and methodologies, like SCRUM or Kanban, and/or lead 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., and following team s established processes and methodologies;
• 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 large scale projects;
• Initiate collaboration with Product Owners, other engineers and data stewards within the team and across data, technical platforms and product teams on planning and aligning roadmaps, delivery dates and integration efforts;
• Coach and mentor junior and aspiring Data Engineers on the team and across the data and engineering communities;
• Facilitate various cross team efforts, like Scrum of Scrums and Release.

KEY TASKS

• Planning, focused on large scale roadmap alignments, sharing information, solving broad variety of problems, or improving processes;
• Effectively discuss work or provide detail to the right level of audience: business partners, data scientists, engineering teams etc;
• Create and maintain design and code documentation in GitHub, Haystack, SharePoint and/or another repositories used by the team;
• Drives mid to long term strategies that support overall technical direction across domain platform;
• Focuses on areas of growth and training for development teams;
• Delivers high quality and scalable architecture designs and code;
• Drives solutions across platform(s) with product management, relevant development teams, software leadership, and business partners, where applicable.

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:

Required qualifications:

• Bachelors degree in Computer Science, Software Engineering, or related field, with 8 years professional software engineering experience or Master's with 5 years of relevant experience or PhD with 3 years of relevant experience;
• Or 12 years of relevant experience is an acceptable substitute for degree requirement;
• Professional software engineering experience to include: at least 5 years experience engineering data intensive software using streaming and resource based design principles;
• At least 3 years experience in least one NoSQL database, such as (but not limited to) Neo4j, Cassandra, etc.;
• At least 5 years 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 Apache Cassandra;
• Strong interpersonal skills and desire to work in a highly collaborative environment;
• Familiarity with the relevant industry trends.

Preferred qualifications:

• Agriculture, life sciences, bioinformatics, biochemistry, genetics, biology, or a related disciplines;
• Platform-as-a-Service software such as Cloud Foundry or Kubernetes;
• Stream processing, e.g. Kafka, Spark Streaming, Akka, etc.;
• Machine learning or other data science practices;
• Experience contributing to open source projects.