In our Location 360 team we believe that the location of things, and the relationships between them in time and space, are of fundamental importance to creating transformational digital products. We are passionate about enabling teams to seamlessly incorporate spatial and location data into their applications, analyses, operations, and models. We do this by ingesting and stewarding much of the location related data for Bayer Crop Science, by integrating models that enrich that data, and by building platforms and interfaces that make it easy for teams to integrate that data into their work. Our Imagery team is looking for an experienced and innovative Full Stack Engineer with cloud proficiency to join us.
As an Imagery Data Engineer, you will play a crucial role in designing, implementing, and maintaining Imagery Team data assets and capabilities in a growing multi-cloud environment to ensure the efficient and reliable operation of Bayer’s Imagery pipelines and services. You will collaborate closely with data engineers, data stewards, data scientists, platform engineers and software developers across the organization to deploy large-scale cloud-based solutions, implement and maintain scalable cloud infrastructures, optimize data pipelines, monitor, and identify issues in the cloud environment, enhance system performance and ensure data integrity and security.
Key responsibilities include:
Work with team and project management to manage priorities, deadlines, and deliverables including collaborative identification and assignment of tasks.
Implement data solutions according to design documentation using a variety of tools and programming languages, like GIT, Kafka, SQL and no-SQL databases, object storage, Python, Typescript/Javascript, C++, Go etc., and following the team’s established processes and methodologies, like SCRUM or Kanban.
Participate in incident response and troubleshooting issues for Imagery data pipelines and API services.
Learn and share code quality practices, and participate in code reviews, retrospectives, functional and integration testing, and other team activities focused on improving quality of delivery.
Assist in developing any technical documentation needed to accurately represent application design and code.
Gain understanding of the business operations and functions for the product(s) owned within the team.
Collaborate with data steward, stake holders, and platform engineers to optimize data pipelines for performance, reliability, and cost-effectiveness.
Actively seek opportunities to discover new and better solutions.
Requirements:
Bachelor’s degree in computer science, Software Engineering, Data Science, or related field including geospatial, environmental, remote sensing/earth observation or other STEM related disciplines
Experience engineering data intensive solutions using streaming and/or resource based (i.e., API) design principles
Experience developing pipeline solutions for deploying to cloud environments like Amazon Web Services, Google Cloud Platform, Azure, etc using respective cloud services like GCS/S3, GCE/EC2, Cloud Functions/Lambda, Pub/Sub/SQS/SNS, GKE/EKS, etc.
Demonstrated understanding of data architecture and modeling, including designing both logical and physical models for datasets
Proven experience writing queries and building data structures from cloud-based datastores like AWS Aurora Postgres, Google BigQuery, Elasticsearch, etc.
Knowledge of at least one NoSQL database such as Elasticsearch, Neo4j, Cassandra, DynamoDB, Spanner, etc.
Experience with containerization technology and orchestration platforms such as Docker and Kubernetes.
Experience with monitoring and logging tools such as Grafana, Prometheus, ELK stack, Datadog or equivalent.
Strong interpersonal skills and desire to work in a fast-paced and highly collaborative environment .
Desirable Qualifications:
Highly proficient in Golang or Python and the respective geospatial libraries associated with each (i.e., GoDAL/GDAL, Rasterio, Pyproj, PDAL, PySTAC, etc.)
Experience with processing UAV (drone) or satellite imagery for modeling and analysis
Experience with cloud-based machine learning platforms (i.e., AWS Sagemaker , Vertex AI, etc.) and familiarity with data science practices , tools, and libraries like Jupyter Notebooks, TensorFlow, PyTorch, Scikit-Learn, Pandas, etc.
Demonstrated experience with Continuous Integration, Continuous Delivery (CICD) concepts and applications like GitHub Actions, Argo, etc.
Proven interest/curiosity in agriculture, life sciences, bioinformatics, biochemistry, environmental sciences, biology, or other STEM related disciplines
Experience working with varied geospatial datasets and formats like WKT, GeoJSON, cloud-optimized GeoTIFF(COGs), OGC services, etc.
Familiarity with Spatio Temporal Asset Catalog (STAC) specification and implementations
Experience building Software Development Kit (SDKs) that advance the adoption of specific software or resource capabilities
Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform.
Experience with standard cloud authentication and authorization patterns
This is a remote position.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
Staffing and Recruiting
Referrals increase your chances of interviewing at Advanced Hires by 2x