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Role Description

This role is a senior technical and strategic leadership position focused on architecting, scaling, and operationalizing modern data and machine learning platforms.

• Lead global, distributed teams to deliver robust cloud-native data solutions and intelligent AI/ML-powered products that drive measurable business outcomes.
• Combine hands-on technical execution with strategic vision, enabling data-driven transformation across diverse industries.
• Partner with cross-functional teams to shape data strategy, embed ML in applications, and ensure solutions are scalable, secure, and high-performing.
• Define best practices, implement cutting-edge technology, and shape a culture of innovation and continuous learning.

Accountabilities

• Lead and mentor global, distributed Data Engineering and Machine Learning teams, fostering a culture of trust, experimentation, and growth.
• Architect and oversee cloud-native data platforms, pipelines, and streaming systems on AWS, Azure, or GCP using technologies such as Databricks, Snowflake, Redshift, BigQuery, Spark, Kafka, Airflow, dbt, and Kubernetes.
• Define and execute responsible ML strategies, integrating AI/ML into applications, analytics, and automation for impactful client outcomes.
• Develop modular engineering frameworks, runbooks, and tooling standards to optimize scalability, observability, and security.
• Partner with Sales, Partnerships, and Account Teams to co-create data & ML solutions that align technical execution with business objectives.
• Translate complex client and business needs into solution designs, proposals, and technical collateral, serving as a trusted advisor in workshops and pitches.
• Collaborate across product, engineering, and operations teams to deliver integrated, end-to-end data and ML solutions.

Qualifications

• 15+ years of experience in data engineering, software engineering, or related technical roles, with 7+ years leading Data Engineering or ML teams.
• Hands-on experience with cloud data platforms, big data toolchains (Spark, Kafka), data orchestration tools (Airflow, dbt), and ML frameworks (SageMaker, Azure ML, TensorFlow).
• Proven experience in designing and scaling modern, cloud-native data architectures and pipelines.
• Strong business acumen with success in pre-sales, solutioning, and growing data/ML engagements.
• Excellent leadership, mentoring, and team-building skills, with the ability to foster inclusive, high-performing engineering cultures.
• Exceptional communication and collaboration skills, able to work effectively across technical, executive, and client-facing environments.
• Demonstrated ability to translate complex technical capabilities into business impact and client solutions.

Preferred Qualifications

• Experience in consulting or global delivery contexts.
• Knowledge of Agile/Lean development, DataOps, MLOps, and CI/CD for data pipelines and models.
• Track record of creating enablement programs, learning paths, and team development initiatives.

Benefits

• Base salary range: $200,000—$240,000 USD.
• Equity opportunities and potential performance-based bonuses.
• Flexible remote-first work model with optional co-working spaces globally.
• Premium health, dental, and vision insurance for employees, with subsidized coverage for dependents.
• Flexible Time Off (PTO) and company holidays.
• 401(k) retirement plan.
• Professional development opportunities, including access to licensed Coursera courses and paid certifications.
• Employee referral programs and global office access program.
• Collaborative, inclusive culture emphasizing autonomy, mastery, and continuous learning.