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Software Engineering Manager (Data and Machine Learning)

Supernatural is helping countless people fall in love with working out for the first time in their lives.

Supernatural harnesses the immersive power of virtual reality to let you travel the world as you smash and box targets to the beat of over 1,000 top hits, coached by a professional trainer. With an ever-growing library of workouts across Supernatural Flow (our original full body cardio modality), Supernatural Boxing, Coach-led Stretch sessions and Guided Meditation, Supernatural invites you to discover your inner athlete and have fun working out. Available on the Oculus Quest.

Check out the Official Supernatural Community on Facebook to meet our diverse community of athletes and coaches as they celebrate their fitness journeys together. Supernatural is loved by The New York Times , Washington Post, GOOP, People, Today, Men’s Fitness, Women’s Health and hundreds more, check out our press page for more.

Join our team and become part of a community dedicated to helping people find joy in health and wellness today.

The Role:

As a Software Engineering Manager you will report to the Director of Engineering, Platform Org and lead the Data Engineering Team.

As a leader of the Data Engineering Team, you will be responsible for managing and growing a team of data engineers and ML engineers to advance our analytics platform and underlying data models to enable advanced reporting, data science analysis and running machine learning models. You will be an integral part in leading a team that will providing data-driven insights that inform significant business decisions, by setting up data infrastructure, building data pipelines, data warehouses, deploying machine learning models to production, and implementing reporting frameworks for different business units.

This role will also facilitate collaboration with adjacent stakeholders in Product, Marketing, Content and Operations teams to deliver the insights and data that drive the growth engine of our business.

In addition to deep and broad software development expertise, the ideal candidate will bring a passion for architecting high-quality solutions that operate with high reliability at scale, and the ability to work non-technical statements of intent into actionable technical plans. We can promise you’ll never be bored!

Responsibilities:

• Collaborate effectively with a multidisciplinary team including Product Managers, Program Managers, Marketing, Content, and Operations stackholders and other roles, across experts and non-experts within the company and the industry and explain complex concepts in a compelling way.
• Stay up-to-date with the state-of-the-art technologies and lead the organization with a culture of learning. Define and evolve engineering standards and best-practices
• Build production grade data and machine learning pipelines in a range of environments, to support batch and streaming applications.
• Implement a robust system for measuring and optimizing the quality of deployed algorithms and models. Institute ML processes for model development with an emphasis on auditability, versioning, and data security.
• Lead the efforts to design and develop data models and applications using selected tools and frameworks.
• Monitor ML models in production to evaluate performance, model drift, and decay.
• Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
• Work closely with the backend and client engineering team to ensure end to end data integrity.
• Provide technical leadership to your team through planning, prioritization, design review and code reviews
• Contribute to all parts of the employee life-cycle, including recruiting, hiring, managing, and mentoring engineers
• Regularly assess and support the team's maturity, health, and composition as you strive for cohesion and technical excellence in delivery
• Ensure objectives are well-understood by all team members
• Lead post-mortems and retrospectives
• Report regularly on progress and share updates
• Help identify, resolve and escalate roadblocks
• Develop positive working relationships with peers and customers
• Foster a growth mindset, regularly seek out opportunities for improvement
• Lead with empathy and understanding, create a safe space to share ideas

Required Qualifications:

• BS or MS degree in Computer Science or related technical discipline, or related practical experience.
• 5+ years experience growing and managing teams of 5 or more people
• 10+ years of engineering experience overall
• 4+ years experience managing Big Data pipelines, as well as custom or structured ETL, implementation, and maintenance
• Capable of managing engineers across multiple disciplines and backgrounds
• Experience with AWS
• Experience running (machine learning) data pipelines
• Exeprience building recommendation engines
• Proficient in writing SQL queries and with data warehousing concepts working on Snowflake etc.
• Strong foundation in software engineering
• Senior level subject matter expertise in one or more languages and disciplines
• Able to mix hands-on technical work with leadership as needed
• Significant experience optimizing software to run fast, be reliable and fail safely – O(n) analysis should be easy for you.

Desired Qualifications:

• Proven track record of launching and supporting live products at scale
• Experience with data processing (such as Hadoop, Spark, Pig, Hive, MapReduce, etc).
• Experience with data modeling tools like dbt is preferred.
• Start-up / entrepreneurial experience

At Supernatural, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Supernatural is committed to bringing together individuals from all different backgrounds and perspectives, however, applicants from agencies as well as corporation to corporation work will not be considered at this time.

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