Lead Data Engineer

Daley and Associates seeks a Lead Data Engineer to specialize in data integration, dbt driven data modeling in Snowflake, and end to end data pipelines for investment data. This on site role in Boston, MA requires three days per week on site, supporting the Investment Data Management Office.

Responsibilities

• Design, develop, and maintain dbt data models in Snowflake, implementing business logic and ensuring alignment with the established data architecture and standards.
• Lead and contribute to dbt projects, ensuring high quality code, thorough documentation, and adherence to modular, scalable design patterns.
• Architect, construct, and manage scalable data pipelines and a robust data warehouse to support reporting, analytics, and operational use cases.
• Lead and participate in development activities; design and implement solutions that address business requirements aligned with program objectives.
• Pursue ongoing enhancements of data quality, resilience, governance, efficiency, and monitoring capabilities.
• Diagnose and resolve complex system interactions to identify root causes of issues.
• Collaborate with the platform lead to design, develop, implement, and deploy new software components for the investment data platform.
• Work with the data architect to evaluate and finalize the unified data model.
• Coordinate with the integration architect to upgrade and integrate ingestion and delivery tools with the unified data platform.
• Upgrade and integrate transformation, data validation, and orchestration tools with the unified data platform to enable data engineering, analytics engineering, and ongoing data maintenance capabilities.
• Provide on call support during unexpected outages.

Requirements

• Bachelor’s degree in Computer Science or a related discipline.
• 5 to 6 plus years of experience designing, developing, and delivering data oriented complex applications.
• Minimum of 2 to 4 years of hands on experience progressing from SQL to Advanced SQL.
• Experience developing and maintaining data models in dbt (Data Build Tool).
• Experience in data integration (ETL/ELT), data warehouse, data analytics architecture, and a solid understanding of design principles; familiarity with Snowflake and other cloud native databases is highly preferred.
• Development experience on cloud based PAAS platforms such as Microsoft Azure, Google GCP or Amazon AWS.
• Strong understanding of Agile SDLC, DevOps, and Cloud technologies, with exposure to multiple technologies, platforms, and processing environments.
• Knowledge of architectures and patterns such as unified data management (UDM), data mesh, event driven architecture, real time data flows, non relational repositories, and data virtualization.
• Experience building solutions in the financial services domain with an understanding of financial instruments, transactions, and positions is desired.
• Strong interpersonal and communication skills with the ability to lead cross team collaboration and partnerships across a variety of internal and external constituencies.

Technologies

• dbt (Data Build Tool)
• Snowflake
• Microsoft Azure
• Google Cloud Platform
• Amazon Web Services

What We Are Looking For

• Bachelor’s degree in Computer Science or related disciplines.
• About five to six years of experience designing, developing, and delivering data oriented complex applications.
• At least two to four years of hands on SQL experience, including advanced SQL techniques.
• Experience in developing and maintaining dbt data models.
• Background in ETL/ELT data integration, data warehousing, and analytics architecture; familiarity with Snowflake and other cloud native databases is highly preferred.
• Development experience on cloud PAAS platforms such as Azure, AWS, or Google Cloud.
• Strong grasp of Agile SDLC, DevOps, and cloud technologies, with exposure to diverse tech stacks and environments.
• Knowledge of architectures like UDM, data mesh, event-driven patterns, real-time data flows, NoSQL stores, and data virtualization.
• Experience delivering solutions in the financial services domain with an understanding of instruments, transactions, and positions is a plus.
• Excellent collaboration and communication skills to coordinate with multiple internal and external stakeholders.

Preferred Qualifications

• Experience within the asset management industry and investment data domain, with exposure to multi asset investment platforms and related data ecosystems.
• Understanding of asset management concepts and knowledge of various financial instruments and products, including traditional and alternative asset classes.
• Industry certifications in Snowflake, dbt, cloud data engineering platforms, data warehousing technologies, or financial markets and operations are highly valued.
• Demonstrated interest in emerging AI technologies and an understanding of how AI driven tools can improve engineering processes, data quality, operational efficiency, and analytics workflows.
• Familiarity with leveraging AI assisted development, automation, or data engineering best practices to enhance productivity and continuous improvement initiatives is a plus.