Job detailsJob TypeContractLocation2067 Westport Center Dr, St. Louis, MO 63146+ Leaflet | OpenStreetMap contributorsIndeed’s salary guideNot provided by employer$95.9K – $121K a year is Indeed’s estimated salary for this role in St. Louis, MO.Report inaccurate salaryFull Job Description

The Data Engineer will be involved in the design of big data solutions that leverage open source and cloud-based solutions within the Location360 enterprise initiative and will work with multiple teams across the organization (i.e. cloud analytics, data architects, business groups). The Data engineer will participate in the building of large-scale data processing systems and API’s and should be able to work with the latest open-source technologies.

A Data engineer should embrace the challenge of dealing with petabytes or even exabytes of data daily in a high-throughput API/microservice ecosystem. A Data engineer understands how to apply technologies to solve big data problems and to develop innovative big data solutions. The Data engineer generally works on implementing complex projects with a focus on collecting, parsing, managing, analyzing and making available large sets of data to turn information into insights using multiple platforms. The Data engineer should be able to develop prototypes and proof of concepts for the selected solutions. This role will drive the engineering and building of geospatial data assets to support Bayer’s Digital Farming Platform and R&D product pipeline.

Key responsibilities include:

Design, build and support of cloud and open-source systems to process data assets via an API-based platform
Partners with other internal development communities to bring needed data sets into the asset and making data available to the Bayer Enterprise and internal development communities
Experience working with ERP/SAP systems
Building highly scalable API’s and associative architecture to support thousands of requests per second
Being able to work across multiple teams internal/external to gather requirements and ensure project development is aligned to those requirements.
Being able to improve the performance of the existing services and be able to identify the scope for any enhancements.
Being able to work with parsing, managing, analyzing and making available large sets of data to turn information into insights using multiple platforms.
Defines and promotes the data warehousing design principles and best practices with regards to architecture and techniques within a fast-paced and complex business environment.
Working at all stages of the software life cycle: Proof of Concept, MVP, Production, and Deprecation

Minimum Requirements:

BSc degree in Computer Science or relevant job experience.
Minimum of 2-year experience with Python/Java development languages.
Knowledge in different programming or scripting languages like Python Scala, Go, Java, Javascript, R, SQL, Bash.
Experience developing HTTP APIs (REST and/or GraphQL) that serve up data in an open-source technology, preferably in a cloud environment.
Ability to build and maintain modern cloud architecture, e.g. AWS, Google Cloud, etc.
Proven experience working with ETL concepts of data integration, consolidation, enrichment, and aggregation. Design, build and support stable, scalable data pipelines or ETL processes that cleanse, structure and integrate big data sets from multiple data sources and provision to integrated systems and Business Intelligence reporting.
Experience working with PostgreSQL/PostGIS.
Experience with streaming sensor/IoT data, e.g. Kafka.
Experience with code versioning and dependency management systems such as GitHub, SVT, and Maven.
Proven success utilizing Docker to build and deploy within a CI/CD Environment, preferably using Kubernetes.

Desirable qualifications:

MSc in Computer Science or related field.
Knowledge on open-source geospatial tech stack such as geoserver.
Highly proficient (4 years) in Python
Experience working with customers/other developers to deliver full-stack development solutions e.g collect software, data, and timeline requirements in an Agile environment.
Demonstrated knowledge on manufacturing facilities and logistics planning.
Experience working with SAP/ERP systems
Experience on implementing scientific models or simulations.
Demonstrated knowledge of agriculture and/or agriculture-oriented businesses.
Experience implementing complex data projects with a focus on collecting, parsing, managing, and delivery of large sets of data to turn information into insights using multiple platforms.
Experience developing schema data models in a data warehouse environment.
Demonstrated experience adapting to new technologies.
Capable to decide on the needed hardware and software design needs and act according to the decisions. The big data engineer should be able to develop prototypes and proof of concepts for the selected solutions.
Experience with object-oriented design, coding and testing patterns as well as experience in engineering (commercial or open source) software platforms and large-scale data infrastructures should be present.
Experience creating cloud computing solutions and web applications leveraging public and private API?s.
Proven experience (2 years) with distributed systems, e.g. Argo, Kubernetes, Spark, distributed databases, grid computing.
Proficient (4+ years) working in a Command Line Interface system e.g Docker, Argo, K8s, AWS CLI, GCloud, pSQL, SSH

IMPORTANT NOTE for POTENTIAL US CANDIDATES: Bayer expects its colleagues to be fully vaccinated against COVID-19. Bayer defines fully vaccinated in alignment with CDC which is two weeks after completing the two-dose vaccine regimen or two weeks after completing the one-dose regimen. Additionally, Bayer colleagues are also required to comply with state, local and customer requirements.

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Hiring InsightsJob activityPosted 30+ days ago

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