Senior Director - Data Engineering & Machine Learning

15+ years in data or software engineering roles 7+ years leading Data Engineering/ML teams Hands-on experience with cloud data platforms Hands-on experience with big data toolchains (Spark, Kafka) Hands-on experience with data transformation tools (Airflow, dbt) Hands-on experience with ML platforms Success in pre-sales, solutioning, and growing data/ML engagements Ability to create enablement programs and uplift team capabilities Ability to grow inclusive, high-performing engineering cultures Deep empathy for client pain points and ability to craft and deliver impactful, measurable solutions Excellent communication and collaboration skills across technical, executive, and cross-functional settings Ability to navigate diverse cultural differences

Design and oversee architecture for cloud-native data platforms, pipelines, and streaming systems on AWS, Azure, or GCP. Ensure robust solutions using platforms such as Databricks, Snowflake, Redshift, BigQuery, Spark, Kafka, Airflow, dbt, and Kubernetes. Define and drive responsible ML strategy, from model development to integration. Enable smarter client experiences by embedding ML into applications, automation, and analytics. Hire, mentor, and empower distributed teams of data and ML engineers. Define career paths, feedback frameworks, and learning programs. Develop modular runbooks, tooling standards, and engineering frameworks. Champion collaborative practices like Agile/Lean development, dataOps, MLOps, and CI/CD. Partner with Sales, Partnerships, and Account Teams to find and co-create data & ML engagements. Translate client needs into solution designs, collateral, and proposals. Serve as a technical leader in pitches, RFPs, and client workshops. Work with product, design, platform, and engineering teams on integrated, end-to-end data solutions. Align with client technical and business stakeholders.