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RemoteFull timeTechnology

Data Science & Engineering Manager

AlltrailsRemote🇺🇸United States

Quick overview

Salary$170k - $215k/yr
SeniorityMid Senior
Employment typeFull Time
Work modeRemote
LocationRemote, United States
RecruitingStakeholder ManagementDockerGCPSQLApache SparkAWSMLOpsSnowflakeAirflowApacheBigQueryComplianceData PipelineGoogle CloudPerformance ManagementPythonStrategic PlanningTerraformdbtKubernetesMachine LearningData AnalysisZoomCI/CD

Job description

AllTrails is the app for exploring the outdoors. We help people spend more time outside by connecting them to their next adventure. Home to the world’s largest outdoor community, with members and trails around the globe, you can find AllTrails in the Apple App Store, Google Play Store, and at alltrails.com.

Every day, our team works to get more people outside and help our members have better experiences on the trail. We lead with our values–positivity, innovation, humility, adaptability, inclusivity, and stewardship–in everything we do. Join us!

This is a U.S. based remote position. While this role does not require in-person attendance, we have a strong preference for candidates based in or near one of these cities: San Francisco CA, Portland OR, Seattle WA, Denver CO, and New York NY. Being in one of these cities creates opportunities to connect with teammates through Trail Days, co-working sessions, and local gatherings while still having the flexibility to work remotely. San Francisco employees are highly encouraged to come to the office one day per week. Please note that, at this time, we’re unable to offer visa sponsorship for this role.

About the role

This role leads a small, centralized engineering function of AllTrails that cross-functionally supports the entire business cross-functionally across separate product, data analytics, finance, and marketing teams. The team sits within the Maps & Data org and reports to the Director of Engineering.

The team's scope spans ownership of scalable data infrastructure, data governance, reliability, compliance, and the development and productionization of machine learning, AI, and algorithmic solutions that power internal operations and member-facing product experiences. A core focus of this role is building and maturing the team's MLOps capabilities, including model deployment pipelines, monitoring, and lifecycle management, alongside a strong foundation in hands-on data pipeline design, development, and operation.

This manager will be both a technical leader and a hands-on practitioner: someone who can roll up their sleeves on pipeline architecture and code reviews while also driving the strategy and culture needed to ship data and ML systems reliably into production.

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

Nature celebrates you just the way you are and so do we! At AllTrails we’re passionate about nurturing an inclusive workplace that values diversity. It’s no secret that companies that are diverse in background, age, gender identity, race, sexual orientation, physical or mental ability, ethnicity, and perspective are proven to be more successful. We’re focused on creating an environment where everyone can do their best work and thrive.

Offers of employment are contingent upon the successful completion of a background check. AllTrails will consider all qualified applicants, including those with arrest and conviction records, in a manner consistent with all applicable laws, including the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act.

AllTrails participates in the E-Verify program for all remote locations.

By submitting my application, I acknowledge and agree to AllTrails' Job Applicant Privacy Notice.

All official recruiting communications from AllTrails will come from an name@alltrails.com email address. Please review sender details carefully, and do not engage with anyone asking for payment or sensitive financial information as part of the hiring process.

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