Engineering Manager - Data & ML

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Engineering Manager - Data & ML in the United States.

As an Engineering Manager - Data & ML, you will lead a high-performing team responsible for designing, scaling, and optimizing a cutting-edge data and machine learning platform. You will play a key role in shaping how data powers products, insights, and decisions across the organization. This hands-on leadership position combines team management with technical ownership, providing opportunities to influence architecture, data quality, availability, and ML workflows. You will collaborate across engineering, product, and analytics teams to build innovative, scalable solutions while fostering a culture of learning, innovation, and operational excellence. Your work will directly impact how the company leverages data for strategic and product decisions in a fast-paced, high-growth environment.

Accountabilities

In this role, you will be responsible for:

• Roadmapping and architecting a scalable data and ML platform to support business needs.
• Establishing best practices for data quality, availability, observability, and governance.
• Designing and implementing optimized data pipelines and ML workflows at scale.
• Managing cloud infrastructure and services for big data and ML workloads, such as SageMaker, Kubeflow, or Vertex AI.
• Leading, mentoring, and scaling a data engineering team, fostering a culture of innovation, learning, and excellence.
• Collaborating with data science, analytics, product, and engineering teams to translate business requirements into technical solutions.
• Staying abreast of emerging technologies and best practices in data processing, storage, and ML development.
• Ensuring robust documentation, testing, and monitoring processes to maintain data integrity and platform reliability.

The ideal candidate will have:

• 8+ years of experience in data engineering, data infrastructure, or machine learning roles, with expertise in architecting near real-time big data systems.
• 2+ years of experience managing teams of 5 or more engineers.
• Proven track record of delivering scalable, innovative solutions leveraging modern data and ML technologies such as Spark, Kafka, Iceberg, and SageMaker.
• Strong hands-on experience with cloud platforms (AWS, GCP, Azure) and distributed computing and storage systems.
• Expert proficiency in Python, SQL, and Infrastructure as Code tools such as Terraform.
• Excellent leadership, communication, and stakeholder management skills.
• Advanced degree in Computer Science, Data Science, or a related field.
• Highly motivated, results-driven, and able to thrive in a fast-paced, entrepreneurial environment.

Preferred qualifications:

• Interest in sports or sports betting.
• Experience building machine learning systems, such as recommendation engines.
• Familiarity with large-scale ML infrastructure and deployment workflows.

This role offers a competitive package including:

• Annual base salary range: $190,000–$220,000, plus equity participation.
• Unlimited paid time off.
• 16 weeks of fully paid parental leave.
• $500 home office allowance.
• 5% 401(k) match, flexible spending accounts, and comprehensive company-sponsored health, dental, and vision coverage for employees and dependents.
• Remote-first, highly engaged, collaborative work culture.
• Opportunities to work on impactful projects at the intersection of data, ML, and product strategy.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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