What you'll be doing
Lead and support a small team of talented data engineers and applied data scientists, fostering their professional growth and ensuring high performance through coaching, performance management, hiring, and team health assessments
Partner with cross-functional stakeholders to understand their needs, translate them into requirements, prioritize work, and communicate progress, risks, and trade-offs across a wide range of business-critical and product-critical data initiatives
Drive data governance, reliability, quality, cost-efficiency, privacy, compliance, and data access best practices across our data platform
Oversee the systems and processes that keep data flowing reliably across the organization, including orchestration, transformation, alerting, and production pipelines.
Own and mature the team's MLOps practice including architecture for model deployment, versioning, monitoring, drift detection, evaluation, retraining, and rollback — turning prototype models into dependable, production-grade systems
Champion the creation of tools to improve data and model cataloging, discoverability, documentation, and self-service to enhance overall democratization of data assets.
Troubleshoot complex data issues, performance bottlenecks, and system failures, providing timely and effective resolutions
Create leverage for the broader organization by improving time-to-insight, time-to-detect, time-to-debug, and overall deployment velocity for data-related work
Act as a thought partner on how AllTrails uses data, AI, and automation to improve internal productivity, trail content, map quality, personalization, and other member experiences
Balance long-term platform investment with near-term delivery needs
Architect, build, and maintain complex data pipelines for both batch and streaming workloads, moving data reliably to and from our data warehouse and operational systems; hands-on participation in research, diagramming, design reviews, code reviews, and on-call rotations is expected
- Research, evaluate, and recommend new data technologies, tools, and platforms to enhance our data capabilities and improve efficiency
- What you bring
- 5+ years of experience in data engineering or ML engineering, with at least 3+ years in managing high-performing data engineering, machine learning, and product-applied data science teams
Comfort leading work across both platform foundations and applied data use cases, with the judgment to prioritize effectively across competing stakeholder needs
Demonstrated, hands-on experience designing, building, and operating complex data pipelines, both batch and streaming, using tools such as Apache Airflow, Apache Spark, Apache Beam, Google Dataflow, or equivalent
Multiple years of experience governing data infrastructure in Google Cloud Platform
Extensive proficiency in transforming and governing high-volume datasets in industry-standard columnar SQL-based warehouses such as BigQuery (preferred) or Snowflake, preferably with experience in ELT tools like Dataform or dbt
Proven expertise in leading the design, development, and maintenance of complex data pipelines using SQL and Python
Solid understanding of best data modeling techniques (e.g. dimensional modeling, star schema, data normalization)
Deep understanding and practical experience in data access patterns, storage solutions, caching, replication, and optimization techniques
Proficiency in containerization and orchestration technologies (e.g., Docker, Kubernetes).
Direct experience leading the software development lifecycle (SDLC) and continuous integration/continuous deployment (CI/CD) practices as they apply to both data pipelines and ML systems
Proven expertise leading the full MLOps lifecycle: model deployment, versioning, monitoring, drift detection, retraining pipelines, and rollback strategies in a production environment
Experience supporting AI/ML use-cases such as personalization, classification, ranking, recommendations, etc.
Willingness to be hands-on and participate in code reviews and an on-call support rotation (currently monthly)
Demonstrated ability to collaborate effectively with diverse stakeholders, translate business requirements into detailed technical specifications, and own projects from inception through successful completion
Strong people leadership skills, including coaching senior ICs, giving clear feedback, growing careers, and building an inclusive, accountable team culture
Comfort operating in a fast-moving environment where you may need to zoom between strategic planning, stakeholder management, and hands-on technical decision-making.
Self-motivation and a deep sense of pride in your team's and your own work
Comfort with ambiguity and an instinct for moving quickly while maintaining high standards.
Humility, empathy, and open-mindedness – a commitment to a collaborative, ego-free environment
- Passion for the outdoors
- Bonus Points
- Experience working with geospatial data, maps, tiling, graph databases, and/or routing
Experience working in a multi-cloud environment (GCP + AWS)
Experience working at a B2C company
- Skilled at managing infrastructure as code (e.g. Terraform)
- Perks & Benefits
- Competitive and equitable compensation, including ownership through equity and performance-based bonuses
Comprehensive health, dental, and vision coverage to support your physical and mental well-being
Unlimited PTO in addition to company holidays
Dedicated time once a month to test and improve our product through company-wide no-meeting days
Fully paid parental leave to birthing and non-birthing parents
401k Match & access to financial wellness resources through Origin
Remote work stipend to help you design a comfortable and productive home office
Annual learning stipend to invest in your long-term professional growth and skills
Exclusive discounts on our subscriptions and merchandise for you and your friends & family
An authentic investment in you as a human being and a professional—we value your identity as much as your output
