Director, Data Engineering (Data Platform)

Asset Mark•Charlotte, NC

61d•$156,000 - $173,000•Hybrid

About The Position

AssetMark is a leading strategic provider of innovative investment and consulting solutions serving independent financial advisors. We provide investment, relationship, and practice management solutions that advisors use in helping clients achieve wealth, independence, and purpose. The Director of Data Engineering & Platform Strategy is a high-impact leadership role that bridges technical execution, architectural vision, and business strategy. This individual will serve as a hands-on technical leader responsible for the end-to-end delivery and operational health of AssetMark's data platform. The role includes direct management of data engineering teams and critical oversight of data governance, security, and the enablement of advanced analytics and AI/ML capabilities. We can consider candidates for this position who are able to accommodate a hybrid work schedule and are close to our Charlotte, NC office.

Requirements

Experience: 10+ years of progressive experience in Data Engineering, Software Architecture, or Technology Leadership, with at least 3+ years in a people management or dedicated technical leadership role.
Hands-on Depth: Proven ability to remain hands-on in design and code architecture reviews. Deep expertise in Python, SQL, and distributed data processing (e.g., Spark/Databricks).
Platform Expertise: Expert-level knowledge of modern cloud data platforms, including Snowflake, Azure Synapse, and/or Azure Fabric.
Financial Domain: Strong preference for experience within the Financial Services, Wealth Management, or FinTech domain, including familiarity with concepts like custodial data, trade processing, and regulatory reporting.
Leadership: Demonstrated success in setting coding standards, leading technical design reviews, and driving technical consensus across multiple development teams.

Responsibilities

Define and Own Data Architecture: Define and drive the multi-year technical roadmap and architecture for AssetMark's enterprise data platform (Data Lakehouse, Data Warehouse, and Operational Data Stores). Ensure all data solutions are scalable, secure, resilient, and align with the enterprise vision (e.g., graph.assetmark.com concepts).
Technical Authority & RFCs: Serve as the final technical authority on data architecture decisions. Lead and author strategic RFCs (Request for Comments) and architectural design reviews (ADRs), ensuring robust, future-proof designs across all data domains.
Build vs. Buy Decisions: Lead the evaluation, selection, and implementation of new data technologies, frameworks (e.g., dbt, data observability tools, vector databases), and vendor solutions, balancing technical fit with financial cost-effectiveness.
Pioneer AI/ML Data Enablement: Architect and implement data pipelines and infrastructure that specifically support data science and AI/ML model training, feature engineering, and inference serving, maintaining strong data governance throughout the lifecycle.
Engineering Oversight: Maintain a hands-on role in core design and code reviews, ensuring technical excellence, adherence to coding standards, and best practices across the engineering teams.
Delivery Management: Oversee the successful, on-time delivery of complex, cross-functional data programs (e.g., major migrations, new product data foundations). Drive agile execution, project planning, and resource alignment for maximum efficiency.
Governance Implementation: Translate data governance principles (data quality, lineage, classification) into automated, enforceable engineering practices within the CI/CD pipeline. Ensure compliance with financial industry regulations (e.g., PII handling, audit trails).
Operational Health: Own the operational reliability, performance monitoring (SLAs/SLOs), and cost management of the data platform. Champion DevOps and Site Reliability Engineering (SRE) practices for data services.
Cross-Functional Collaboration: Act as the primary liaison and technical partner, collaborating closely with Product Managers to define requirements, Software Engineering teams to ensure data service interoperability, and Senior Business Stakeholders to align data initiatives with commercial priorities.
Partner Management: Manage strategic relationships with critical external vendors, technology partners, and data providers (e.g., custodians, cloud vendors), ensuring favorable contracts and optimizing data acquisition strategies.
Talent & Mentorship: Build, mentor, and lead a high-performing team of data engineers and architects, fostering a culture of ownership, technical rigor, and continuous learning. Guide career development and succession planning within the data engineering function.