What you'll do:

• Perform technical design and hands-on development of enterprise-scale geospatial and geometric data pipelines and repository services
• In partnership with data and enterprise architects, design and implement pipeline capabilities, data taxonomies, and API payload definitions using best practices and industry standards
• Lead and/or actively participate in team technical activities including story breakdown sessions, sprint planning, effort estimation, code reviews, NFR assessments, and architectural reviews
• Actively evaluate, prototype, and recommend next-generation cloud-native data pipeline and data repository technologies
• Identify and implement data quality management capabilities, AI-based monitoring tools, and associated governance controls/reporting
• Participate in the troubleshooting and RCA process for production issue escalations
• Create clear and concise technical documentation, production support runbooks, and supporting quality metrics
• Assess, refactor, and optimize high-volume repository transaction and distribution channels.

What makes you a great fit:

• 10+ years of professional experience building enterprise-scale real-time and batch-based data pipelines and data distribution (serving) capabilities.
  
• 5+ years developing and delivering high-volume data processing solutions within a cloud-native environment, preferably AWS
• 2+ years in a technical leadership role within a technology or data product organization
• Deep experience leveraging modern open-source data processing/data pipeline technologies, frameworks, and cloud tools (S3, Lambda, Spark, Kinesis, Kafka, Airflow, Steps, etc.)
• Experience working with geospatial/geometric datasets and geospatial/vector data stores
• Previous experience building enterprise-caliber, event-driven distributed systems using cloud-based architectural patterns and infrastructure
• Intimate familiarity with cloud-based open-source SQL and NoSQL databases including experience in performance tuning and query optimization
• Familiarity with domain-based data architecture, metadata management, machine learning environments, and data quality frameworks
• Test-driven development mindset with a focus on data quality, services scalability, and code efficiency
• Previous experience with Functional programming methods using modern development languages (Go, Scala, etc.) is preferred
• Previous direct collaboration with US-based engineering resources is a plus
  
• Collaborative working style with a primary focus on the predictable delivery of quality outcomes.
• Experience working within governed Enterprise Agile planning and delivery organizations using Scrum practices preferred