Bachelor's degree in Computer Science, Engineering, or relevant job experience with 5+ years
Strong proficiency in Infrastructure as Code (IaC) principles and tools (i.e. Terraform, GCDM, CloudFormation, Docker compose, etc.)
Strong understanding and hands-on experience with CI/CD tools such as GitHub Actions, Terraform, Google Cloud Build, ArgoCD
Strong proficiency in Python and/or Go programming languages
Hands-on experience working with Kubernetes(K8s) for orchestrating and managing containerized data services and workflows.
Proven experience with SQL databases and/or BigQuery, including schema design and query optimization
Hands-on experience with event-driven and streaming data architectures using platform and services such as Kafka, AWS SQS, and Google Cloud Pub/Sub
Ability to work in a highly collaborative environment and to communicate effectively with internal and external partners
Experience working with and testing high-volume RESTful APIs deployed on common cloud Kubernetes infrastructures
Experience with utilizing Docker to build and deploy containerized applications
Experience with telemetry data flows and monitoring and logging tools such as Grafana, Prometheus, ELK stack, or equivalent.
Experience in cloud platforms such as GCP and AWS, including native data and compute services such as Bigquery/Aurora, GCS/S3, GKE/EKS, GCE/EC2, Cloud Functions/Lambda
Experience with code versioning and dependency management systems such as GitHub
Excellent problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.
Strong communication skills and the ability to articulate technical concepts to non-technical stakeholders.
Preferred:
Highly proficient (5+ years) in Python or Golang with a strong track record of maintaining production data pipelines and backend systems
Experience with PostgreSQL/PostGIS enabled databases
Experience scaling GRPC services, working with protobuf schemas and tooling such as BSR
Experience with object-oriented design, coding and testing patterns, and implementing complex data projects in a large-scale data infrastructure
Understanding of geospatial data concepts. Experience with data processing and analysis using geospatial libraries and tools
Familiarity with cloud-based machine learning services and platforms such as Google Cloud Vertex AI or AWS SageMaker. Experience with deploying invoking model endpoints.
Solid understanding of networking concepts, security principles, and best practices for cloud environments
Experience working with customers and developers to deliver full-stack development solutions; the ability to translate customer requirements into technical requirements in an Agile environment
Offer description
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.
We are looking for a Data Engineer - Site Reliability!
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 squad is looking for an experienced and innovative SRE/DevOps Engineer to join us.
As an SRE you will partner with Imagery squad engineers to bridge software engineering and system administration with a focus on ensuring the reliability, availability, and performance of software systems operating on common cloud infrastructures. You will proactively monitor cloud-enabled imagery pipelines and drive continuous improvement initiatives to gain efficiencies and minimize system down time. You’ll work closely with data engineers, cloud engineers, data stewards, software developers, data scientists and domain experts to build observable and scalable cloud-based infrastructures using modern cloud-native and open-source Infrastructure as Code (IaC) technologies.
WHAT DO WE OFFER:
A flexible, hybrid work model
Great workplace in a new modern office in Warsaw
Career development, 360° Feedback & Mentoring programme
Wide access to professional development tools, trainings, & conferences
Company Bonus & Reward Structure
Increased tax-deductible costs for authors of copyrighted works
VIP Medical Care Package (including Dental & Mental health)
Holiday allowance (“Wczasy pod gruszą”)
Life & Travel Insurance
Pension plan
Co-financed sport card - FitProfit
Meals Subsidy in Office
Budget for Home Office Setup & Maintenance
Access to Company Game Room equipped with table tennis, soccer table, Sony PlayStation 5 and Xbox Series X consoles setup with premium game passes, and massage chairs
Tailored-made support in relocation to Warsaw when needed
Please send your CV in English
WORK LOCATION: WARSAW AL. JEROZOLIMSKIE 158
Your responsibilities
Drive continual improvement in deployment, observability, monitoring, and scalability
Automate tasks to improve efficiency, manage infrastructure, and ensure performance of Loc360 assets that meet or exceed stated SLOs
Assist developers implementing scalable data pipelines in Python and Go for ingestion, transformation, and delivery of structured and unstructured geospatial data.
Write and review code, develop documentation, and debug complex problems between systems and components.
Optimize event-driven data processing solutions using Kafka, AWS SQS, and Google Cloud Pub/Sub to orchestrate multi-stage spatial workflows.
Integrate and manage data flows across cloud platforms such as AWS and GCP, databases such as PostgreSQL/PostGIS and BigQuery, and cloud storage such as AWS S3 and Google Cloud Storage