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About
Location:
Hybrid (Atlanta, GA preferred)
About AssetMark: AssetMark is a leading strategic provider of innovative investment and consulting solutions serving independent financial advisors. We empower advisors with investment, relationship, and practice management tools that help their clients achieve wealth, independence, and purpose.
The Role:
As a
Lead Data Engineer , you will play a pivotal role in designing and managing AssetMark's modern data infrastructure. You will help shape and execute the data strategy that enables trusted, scalable, and high-performing solutions across the organization. Your work will directly support AssetMark's mission to deliver data-driven wealth management services through innovation, governance, and collaboration.
Key Responsibilities: Define, document, and manage the enterprise data strategy, including schema design, SLAs, data contracts, security, and compliance. Evangelize best practices across data architecture and data engineering disciplines, particularly in
wealth management and financial services
domains. Lead and grow a high-impact data engineering team responsible for platform performance, CI/CD, and operational excellence. Own the implementation roadmap for continuous improvements, including
Azure/Fabric-based modernization , compliance, and cost optimization. Ensure robust platform reliability through automated test cases for performance, security, and scalability. Partner cross-functionally with analytics, business, and technology teams to align on architecture, governance, and delivery timelines. Manage and optimize ingestion, transformation, and curation of large-scale
structured and unstructured datasets . Develop reusable data components and pipelines to support enterprise reporting, BI, and advanced analytics. Champion
DataOps, metadata management, monitoring, alerting , and
data quality frameworks . Advocate for scalable modeling practices including
semantic layer design
and
preferred Data Vault 2.0 methodology
for enterprise architecture. Required Skills & Expertise:
Strong leadership, communication, and cross-team collaboration skills. Extensive experience building data platforms in Microsoft
Azure , including tools like
Azure Synapse, Data Lake, Data Factory , and
Microsoft Fabric . Demonstrated success delivering data engineering solutions in the
wealth management or financial services industry . Expertise with modern architectural concepts:
Lakehouse, Data Mesh, Data Fabric, and ELT/ETL orchestration . Proven ability to deliver analytical data products across domains such as Finance, Product, Sales, and Marketing. Hands-on experience with
data modeling, data cataloging, lineage tracking , and
governance . Proficient in
CI/CD , Agile methodologies, and working within enterprise-scale cloud environments. Preferred experience with
Data Vault 2.0 modeling
for building scalable, auditable data systems. Familiarity with
Salesforce, Yardi , and other domain-specific systems is a plus. Preferred Qualifications:
Strong architectural knowledge of
Microsoft Fabric and Azure-native analytics stack . Microsoft Azure Certification or similar cloud credentials. Familiarity with applying
AI/ML frameworks
to business problems is a plus. Strong ability to interpret and present data-driven insights to stakeholders at all levels. Education & Experience:
12+ years
in IT with a focus on data engineering, systems design, or data architecture. 5+ years
in a data architect or lead engineer capacity with increasing responsibility. Bachelor's degree in computer science, Information Systems, or a related field (master's preferred).
Languages
- English
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