Senior/Staff Data Engineer IV

Autonomous Solutions • Longmont, CO

6d

About The Position

The Senior/Staff Data Engineer IV designs, builds, and owns the data systems that turn information from ASI's autonomous vehicle platforms, field operations, fleet activity, telemetry, business systems, and third-party sources into reliable, trusted data for the company. This role sits at the intersection of robotics, cloud infrastructure, data engineering, and business operations, helping teams understand fleet performance, vehicle usage, system health, customer activity, and operational trends.
This is a high-ownership, hands-on engineering role for someone who is strong in Python and SQL and comfortable building production data systems that are reliable, observable, scalable, and easy for others to use. The role partners closely with software, autonomy, field operations, product, customer-facing, finance, and leadership teams to create durable data pipelines, models, and tools that support internal reporting, customer-facing products, operational decision-making, and business-critical workflows.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Data Engineering, Information Systems, Mathematics, Statistics, or a related technical field
• Typically 5+ years of professional experience in data engineering, software engineering, analytics engineering, or related data-platform work; Staff-level candidates will typically bring deeper architecture ownership and broader technical leadership experience
• Strong proficiency with Python and SQL
• Experience building and operating production data pipelines and large-scale data systems
• Experience with cloud data warehouses such as Snowflake, Redshift, BigQuery, or similar platforms
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or similar systems
• Experience with orchestration, transformation, or workflow tools such as Airflow, Dagster, dbt, Luigi, or similar frameworks
• Experience designing data models that support analytics, reporting, operations, product workflows, or financial processes
• Experience implementing data-quality checks, tests, monitoring, alerting, and observability for production data systems
• Ability to reason through data correctness across multiple systems, pipelines, schemas, and business workflows
• Experience troubleshooting production data issues and following problems through to resolution
• Ability to communicate clearly with both technical and non-technical stakeholders
• Experience enabling self-service data access through documentation, curated datasets, reporting tools, or data products
• Strong software engineering fundamentals including version control, code review, testing, deployment practices, and maintainable design
• Ability to work independently, prioritize effectively, and make pragmatic technical decisions in a fast-moving environment

Nice To Haves

• Experience working with telemetry, streaming data, event-driven systems, IoT data, robotics data, or data from connected physical machines
• Experience with geospatial data, time-series data, vehicle data, sensor data, or system log data
• Experience supporting data-intensive products, customer-facing platforms, fleet-management tools, or operational dashboards
• Experience with AWS services such as S3, Glue, Lambda, ECS, RDS, Redshift, Kinesis, or similar cloud services
• Experience with Docker, ECS, Kubernetes, or other containerized deployment environments
• Experience integrating third-party APIs and external data sources
• Experience supporting usage-based billing, customer reporting, financial workflows, or business-critical operational systems
• Experience with BI tools such as Tableau, Power BI, Looker, Sigma, Metabase, or similar tools
• Experience with Infrastructure as Code, CI/CD pipelines, or cloud deployment practices
• Experience working with autonomous vehicles, robotics, heavy equipment, industrial systems, or fleet operations

Responsibilities

• Build, maintain, and optimize production data pipelines that ingest, transform, validate, and publish fleet, telemetry, operational, business, and third-party data
• Design data models that support reporting, analytics, customer-facing products, operational workflows, and business-critical decision-making
• Own the systems that turn autonomous vehicle activity into trusted usage, performance, and operational data
• Develop and maintain data pipelines using Python, SQL, orchestration tools, transformation frameworks, and cloud data platforms
• Optimize existing pipelines for performance, reliability, scalability, and cost efficiency as data volume and business needs grow
• Improve data quality through automated testing, validation checks, monitoring, alerting, and incident response processes
• Build observability into data systems so pipeline failures, data-quality issues, latency problems, and schema changes are identified quickly
• Partner with engineering teams to understand vehicle telemetry, robotics data, system logs, and operational context
• Partner with fleet operations, product, finance, customer success, and leadership teams to translate business questions into durable data systems
• Support internal reporting and self-service analytics by creating reliable datasets, documentation, dashboards, and data access patterns
• Develop systems that support workflows such as fleet performance analysis, utilization tracking, customer reporting, usage-based billing, and operational planning
• Integrate data from APIs, cloud services, relational databases, robotics systems, business tools, and third-party platforms
• Create and maintain data documentation, lineage, ownership, quality expectations, and definitions for key business and operational metrics
• Support data governance, security, access control, and privacy practices for company and customer data
• Troubleshoot pipeline failures, data inconsistencies, performance bottlenecks, and production data incidents
• Collaborate with backend, cloud, robotics, product, and operations teams to ensure data systems are aligned with product and platform needs
• Provide hands-on technical leadership for data architecture, implementation standards, code quality, reliability, and maintainability
• Review data models, pipeline designs, and code from other engineers and provide constructive technical feedback
• Evaluate and recommend tools, frameworks, and architectural improvements for the data platform
• Support the development of scalable data practices that help non-technical users safely and confidently access the data they need

Benefits

• 401k with employer match
• Generous HSA contribution
• Employee Stock Options
• PTO, paid holidays, and flextime
• ASI covers 90% of employee medical plan costs

What This Job Offers

• Job Type: Full-time
• Career Level: Senior