Lead Data Engineer/Architect

Overview

Hybrid
Depends on Experience
Full Time
No Travel Required

Skills

Advanced Analytics
Analytical Skill
Extract
Transform
Load
Wealth Management
Roadmaps
Optimization
Orchestration
Meta-data Management
Financial Services
Leadership
Machine Learning (ML)
Data Lake
Data Modeling
ELT
Continuous Delivery
Continuous Integration
Data Architecture
Data Engineering
Enterprise Architecture
Automated Testing
FOCUS
Artificial Intelligence
Finance
Business Intelligence
Cloud Computing
Collaboration
Communication
Management
Marketing
Microsoft
Microsoft Azure
Modeling
Operational Excellence
Pivotal
Regulatory Compliance
Reporting
Sales
Salesforce.com
Scalability
Semantics
Systems Design
Yardi
Analytics
Agile

Job Details

Position: Lead Data Engineer/Architect

Location: Atlanta, GA (Hybrid)

Experience: 15+ Years

Job Type: Full Time

Must Have: Data Vault, Microsoft Azure, Data Vault, wealth management or financial services industry.

  • Responsibilities:

    As a Lead Data Engineer, you will play a pivotal role in designing and managing company'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 company'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).

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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