Lead client-facing data engineering initiatives, designing scalable data pipelines, architectures, models, and schemas. Translate business requirements into technical solutions, optimize data delivery and automation, mentor engineering teams, and support project planning, proposals, estimation, and solution delivery. Work with technologies including Databricks, Spark, Snowflake, Airflow, Kafka, cloud services, SQL, and programming languages such as Python, Scala, Java, and C++. Travel averages 30–50%, with home-office work when not at client sites.