Lead Data Engineer

As a Senior Data Engineer, you will play a pivotal role in designing and managing client 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 client 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.