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 Experience with big data toolchains (Spark, Kafka) Experience with data transformation tools (Airflow, dbt) Experience with ML platforms Success in pre-sales, solutioning, and growing data/ML engagements Demonstrated ability to create enablement programs and uplift team capabilities Deep empathy for client pain points Excellent communication and collaboration skills

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, using platforms like SageMaker, Azure ML, or TensorFlow. Foster a culture of trust, continuous learning, and experimentation by hiring, mentoring, and empowering distributed teams of data and ML engineers. Develop modular runbooks, tooling standards, and engineering frameworks optimizing for scalability, observability, and security. Champion collaborative practices like Agile/Lean development, dataOps, MLOps, and CI/CD for data pipelines and models. Partner with Sales, Partnerships, and Account Teams to find and co-create thoughtful, outcome-driven data & ML engagements. Translate client needs into solution designs, shareable collateral, and winning proposals and estimates. 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.