• Lead and manage the Azure DataOps function, ensuring smooth daily operations, incident resolution, and performance stability across production data platforms. • Oversee data pipeline orchestration and automation using Azure Data Factory (ADF), Synapse Analytics, Databricks, and Logic Apps. • Implement CI/CD pipelines for data workflows using Azure DevOps or equivalent automation tools. • Drive incident, problem, change, and request management processes aligned with ITIL best practices. • Coordinate with L1/L2 support teams for escalations, RCA preparation, and client communication. • Maintain governance for data quality, access control, and compliance using Azure Purview, Key Vault, and RBAC. • Collaborate with Data Architects and Cloud Engineers to design scalable, resilient, and cost-efficient Azure data solutions. • Ensure 24/7 operational readiness through proactive alert monitoring, performance tuning, and preventive maintenance. • Contribute to automation initiatives using PowerShell, Python, or ARM templates to reduce manual efforts and improve system reliability. • Partner with customer stakeholders to report on SLAs, KPIs, RCA summaries, and provide technical recommendations for improvement. • Support onboarding and knowledge transition for new clients and ensure documentation consistency across environments. • Mentor and upskill the DataOps L1/L2 teams, fostering a culture of ownership, accountability, and process discipline.

• The Data engineer - IV is responsible for managing and operating upon Tableau, Tableau bridge server, Databricks, Dbt, SSRS, SSIS, AWS DWS, AWS APP Flow, PowerBI. • Leads operational coverage: • Resolving pipeline issues / Proactive monitoring for sensitive batches / RCA and retrospection of issues and documenting defects. • Design, build, test and deploy fixes to non-production environment for Customer testing. • Work with Customer to deploy fixes on production upon receiving Customer acceptance of fix. • Cost / Performance optimization and Audit / Security including any associated infrastructure changes. • Knowledge Management: Create/update Knowledgebase/ runbooks as needed. • Governance: Watch all the configuration changes to batches and infrastructure (cloud platform) along with mapping it with proper documentation and aligning resources. • Change Management: Align resources for on-demand changes and coordinate with stakeholders as required. • Incident Management and Problem Management, Root cause Analysis, coming up with preventive measures and recommendations such as enhancing monitoring or systematic changes as needed.

• Resolving pipeline issues / Proactive monitoring for sensitive batches / RCA and retrospection of issues and documenting defects • Design, build, test and deploy fixes to non-production environment for Customer testing • Work with Customer to deploy fixes on production upon receiving Customer acceptance of fix • Cost / Performance optimization and Audit / Security including any associated infrastructure changes • Knowledge Management: Create/update Knowledgebase/ run books as needed • Governance: Watch all the configuration changes to batches and infrastructure (cloud platform) along with mapping it with proper documentation and aligning resources • Communication: Lead and act as a POC for customer from on-site, handling communication, escalation, isolating issues and coordinating with off-site resources while level setting expectation across stakeholders • Change Management: Align resources for on-demand changes and coordinate with stakeholders as required • Request Management: Handle user requests – if the request is not runbook-based create a new KB or update runbook accordingly • Incident Management and Problem Management, Root cause Analysis, coming up with preventive measures and recommendations such as enhancing monitoring or systematic changes as needed.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Blue River Technology — the team behind John Deere's See & Spray™ — uses computer vision and machine learning to help farmers reduce herbicide use and grow smarter. Our ML Platform team needs a Data Engineer to keep that intelligence flowing. What you'll do: - Own data pipelines end-to-end — ingestion, quality, performance, and reliability - Optimise queries and shape data architecture across the ML development lifecycle - Build and maintain ETL workflows that feed annotation, exploration, and model training - Support infrastructure scalability across AWS (S3, DynamoDB, Lambda, SQS, and more) - Improve code quality through automation, testing, and peer reviews - Collaborate directly with roboticists, backend engineers, and platform teams Qualifications - 2+ years in backend engineering / data infrastructure - Strong Python skills - Hands-on experience with ETL pipelines and data architecture - Solid grasp of relational and non-relational databases - AWS services (S3, DynamoDB, EC2, Lambda, ECR, SQS, SNS) - Docker + CI/CD (GitHub Actions or Jenkins) - Clear communicator who documents well and works cross-functionally - BS or MS Computer Science Requirements - Bonus points for Databricks / Apache Spark - Kubernetes in production - Terraform or CloudFormation Benefits - This is a contractor role working with a small, collaborative team of 5 - Location preference is North America, Pacific time zone - Hourly Rate starting at $70/hour