Sr. Manager, Data Engineering

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

Trade Station is the home of those born to trade. As an online brokerage firm and trading ecosystem, we are focused on delivering the ultimate trading experience for active traders and institutions. We continuously push the boundaries of what's possible, encourage out-of-the-box thinking, and relentlessly search for like-minded innovators.

At Trade Station, we are building an AI-First culture. We expect team members to embrace AI as a core part of their daily workflow, whether that's using AI to accelerate development, enhance decision-making, improve client outcomes, or streamline internal processes. We hire, grow, and promote people who can harness AI responsibly and creatively. We treat AI as a partner in problem-solving, not just a tool;

following our governance standards to ensure AI is used ethically, securely, and transparently. If you join us, you're joining a culture where AI is how we work.

Are you ready to make yourself at home?

We are looking for a Senior Manager of Data Engineering who will play a pivotal role in our organization, leading the Data Engineering team and ensuring the secure, efficient, and seamless handling of our organization's data assets. With Databricks as our primary SaaS platform, this role owns and manages our end-to-end Databricks environment and will focus on designing and implementing robust data infrastructure including Databricks AI capabilities and AI/BI Genie apps to support business operations, analytics, and innovation.

Partnering closely with business and product management, the Senior Manager will help define and drive both the technical and business data roadmap. The successful candidate will possess strong leadership skills, deep knowledge of data and AI infrastructure, and a drive to enhance the data-driven nature of our business. This position combines technical expertise with strategic oversight, enabling the team to deliver scalable, high-performing data solutions aligned with organizational goals.

Bring your passion and skills to solve interesting problems and have an immediate impact. Join us!

Leadership & Team Management
:

• 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

Secure and Efficient Data Handling
:

• Implement and maintain data governance frameworks to ensure data integrity, security, and compliance
• Collaboration and Business Impact:
• 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

Project Management
:

• Prioritize and manage multiple data engineering projects,…