Principal Machine Learning Data Engineer

Digital Turbine•New York, NY

1d•Hybrid

About The Position

Digital Turbine aims to make mobile advertising experiences more meaningful and rewarding for users, app publishers, and advertisers by intelligently connecting people across various devices. The company provides powerful ads and experiences that captivate consumers, fuel performance, and help telecoms and OEMs enhance awareness, acquisition, and monetization. In a rapidly evolving industry, Digital Turbine continuously innovates to create better paths of discovery for consumers, publishers, and advertisers within the mobile ecosystem. The Principal Machine Learning Data Engineer is a senior technical expert and thought leader responsible for defining the direction for data and ML platforms and resolving complex, high-impact engineering challenges. This role involves setting technical strategy, influencing organizational architecture, and ensuring that data and ML capabilities support long-term business growth. The work is highly self-directed, with evaluation based on outcomes and strategic impact.

Requirements

Typically 12+ years of experience in data/ML engineering or closely related disciplines, with extensive experience as a senior/lead/principal engineer
Recognized internally as a subject-matter authority in data and ML engineering
Applies a systems-thinking approach to complex, ambiguous problems, balancing technical, product, and organizational constraints
Influences at senior leadership levels and across functions, often driving consensus in areas of disagreement
Communicates with clarity and impact in both technical and non-technical settings, tying technical choices to business outcomes
Operates with a high degree of autonomy, setting direction and driving outcomes across teams
Deep expertise in large-scale data and ML architectures, including streaming, batch, real-time serving, and advanced analytics
Proven track record of designing and delivering complex, distributed systems in production at scale
Expert-level proficiency in at least one language used for data and ML engineering (Python, Scala, or Java) and advanced SQL
Demonstrated experience setting technical strategy, defining architectures, and influencing multiple teams and stakeholders
Experience in environments with very large data volumes and real-time decisioning (e.g., AdTech, recommendations, marketplaces, personalization)

Nice To Haves

Contributions to open-source data or ML projects, or recognized thought leadership (talks, publications, etc.)

Responsibilities

Define and drive the long-term architecture and strategy for data and ML platforms, including data infrastructure, feature platforms, and model serving
Lead design and delivery of mission-critical, cross-organizational data and ML solutions that require deep technical expertise and strong stakeholder alignment
Serve as a hands-on expert on complex initiatives, providing guidance on system design, performance, scalability, and reliability
Partner with senior leadership to identify new opportunities where data and ML can unlock business value and competitive advantage
Establish and evangelize best practices, patterns, and standards for data and ML engineering, influencing multiple teams and domains
Mentor and develop senior and lead engineers, raising the overall technical bar of the organization
Evaluate and introduce emerging technologies, frameworks, and tools in data and ML engineering, making build/buy/partner recommendations
Represent the organization in high-stakes technical discussions, reviews, and external forums as appropriate
Operate within a marketplace AdTech environment — spanning demand-side optimization, supply monetization, and data pipeline architecture at scale
Directly own systems or products that sit across the full AdTech stack: bidding infrastructure, yield management, audience data, and measurement