Sr. Manager, Data Engineering

TradeStation is an online brokerage firm and trading ecosystem focused on delivering trading experiences for active traders and institutions. The Senior Manager of Data Engineering will lead the data engineering team, own the end-to-end Databricks environment, and drive secure, scalable data infrastructure, AI capabilities, and analytics solutions. The role also partners with business and product management to define and execute the technical and business data roadmap.

Responsibilities:

• Manage, mentor, and inspire a team of skilled data engineers to deliver high-quality work
• Provide direction, performance feedback, and career development opportunities
• Foster a culture of collaboration, innovation, and continuous learning
• Manage the design and implementation of scalable and efficient data pipelines on Databricks
• Define and implement data architecture to support both batch and real-time data processing
• Leverage Databricks features (e.g., Delta Lake, Databricks SQL, MLflow) to optimize infrastructure for performance and cost
• Own, administer, and continuously optimize the end-to-end Databricks environment, including workspace administration, cluster and compute management, Unity Catalog governance, and cost/performance monitoring
• Build and operationalize Databricks AI capabilities (Mosaic AI, model serving, and generative AI/agent workflows) to power intelligent, data-driven products
• Design, deploy, and maintain AI/BI Genie spaces and Genie-powered apps that enable business users to explore data and get answers through natural-language conversation
• Implement and maintain data governance frameworks to ensure data integrity, security, and compliance
• Partner with data scientists, analysts, and business teams to enable data-driven decision-making
• Work closely with business and product management to define, prioritize, and own both the technical and business data roadmap, aligning platform investments with organizational strategy
• Translate business needs into technical requirements and scalable data solutions
• Communicate technical plans, challenges, and achievements to stakeholders at all levels
• Prioritize and manage multiple data engineering projects, ensuring timely delivery
• Define success metrics and continuously track progress to achieve desired outcomes
• Stay informed on industry trends, particularly advancements in Databricks, Databricks AI (Mosaic AI, AI/BI Genie), generative AI, and cloud-based data platforms
• Establish and enforce best practices for coding, testing, and deploying data engineering solutions

Requirements:

• Remote Position - must reside Florida, Texas, Illinois, New York, New Jersey, Alabama, Arizona, Arkansas, Colorado, Connecticut, Delaware, Georgia, Indiana, Kansas, Massachusetts, Missouri, North Carolina, Tennessee, Utah or Wisconsin
• Proven experience running projects and managing direct reports
• Knowledge of data governance practices, business and technology issues related to managing enterprise information assets, and approaches related to data protection
• Knowledge of industry-leading data quality and data protection management practices
• Strong analytical, technical, oral, and written communication skills
• Strong knowledge of database design, data warehousing, and ETL processes
• Ability to present projects to technical and non-technical staff
• Team player who can work flexible hours
• Expertise in Databricks and its ecosystem (Delta Lake, Spark, Databricks SQL, MLflow, etc.)
• Hands-on experience with Databricks AI, including Mosaic AI, model serving, and generative AI/agent solutions
• Experience building and deploying AI/BI Genie spaces and Genie apps to deliver natural-language, self-service analytics to business users
• Experience administering and managing a Databricks environment, including workspace/cluster management, Unity Catalog, security, and cost governance
• Proficiency in programming languages such as Python, Scala, or SQL
• Experience with cloud platforms (AWS, Azure, or GCP) and associated data services
• Strong understanding of ETL processes, data pipelines, and real-time data streaming
• Knowledge of data modeling, database design (relational and non-relational), and optimization techniques
• Bachelor's degree in computer science/Engineering or equivalent work experience
• Must have 5+ years of technology industry experience
• Comfortable with writing scripts and using command-line interfaces preferred
• Knowledge of full-stack monitoring concepts and tooling from code to system resources preferred
• Programming Skills – knowledge of statistical programming languages like R, and Python and database query languages like SQL preferred
• Data Wrangling – proficiency in handling imperfections in data preferred
• Strong software engineering background preferred
• Experience in Databricks AI capabilities and AI/BI Genie solutions into a production environment preferred
• Prior experience owning a data platform roadmap in partnership with product management in a financial services or brokerage environment preferred
• Databricks certification(s), such as Databricks Certified Data Engineer Professional or a Databricks Generative AI / Machine Learning certification
• 7+ years of technology industry experience with prior people-management experience leading a data engineering team