Lead Data Engineer

Daley and Associates is seeking a Lead Data Engineer to own the development of data integration, dbt-driven data modeling in Snowflake, and the construction of end-to-end data pipelines that empower investment data analytics. This onsite role in Boston, MA requires a collaborative leader who can support the Investment Data Management Office three days per week while driving scalable solutions that align with architectural standards.

Responsibilities

• Develop and maintain dbt models inside Snowflake, embedding business logic and ensuring alignment with the existing architecture and data standards.
• Oversee and contribute to dbt projects, maintaining code quality, documentation, and modular, scalable design patterns.
• Design, build, and administer scalable data pipelines and a robust data warehouse to support reporting, analytics, and operational use cases.
• Lead development efforts and implement solutions that meet business requirements and support program objectives.
• Drive continuous improvement of data quality, resiliency, control, efficiency, and monitoring capabilities.
• Troubleshoot complex system interactions to identify root causes of issues.
• Collaborate with the platform lead to design, develop, implement, and deploy new software components on the investment data platform.
• Partner with the data architect to evaluate and finalize a unified data model.
• Work with the integration architect to upgrade and integrate data ingestion and delivery tools within the unified platform.
• Upgrade and integrate transformation, data validation, and orchestration tools to enable data engineering, analytics, and maintenance tasks.
• Provide on-call support during unexpected outages.

Requirements

• Bachelor’s degree in Computer Science or related disciplines.
• 5-6+ years designing, developing, and delivering data-centric, complex applications.
• 2-4+ years of hands-on work from SQL to Advanced SQL.
• Experience developing and maintaining data models using dbt (Data Build Tool).
• Background in data integration (ETL/ELT), data warehousing, analytics architecture, with familiarity in Snowflake and other cloud-native databases.
• Development experience on cloud PAAS platforms such as Microsoft Azure, Google Cloud Platform, or Amazon Web Services.
• Strong understanding of Agile SDLC, DevOps, and cloud technologies, with exposure to multiple technologies and environments.
• Knowledge of architectures and patterns such as unified data management, data mesh, event-driven architectures, 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 desirable.
• Solid interpersonal and communication skills with the ability to lead cross-team collaborations.

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.
• 5-6+ years designing, developing, and delivering data-oriented, complex applications.
• 2-4+ years of progressive SQL experience, including advanced SQL.
• Proven experience developing and maintaining data models with dbt.
• Background in data integration (ETL/ELT), data warehousing, and analytics architecture; familiarity with Snowflake and other cloud-native databases.
• Experience developing on cloud PAAS platforms such as Azure, GCP, or AWS.
• Deep grasp of Agile SDLC, DevOps, and cloud technologies, with exposure to diverse technologies and environments.
• Knowledge of unified data management, data mesh, event-driven, real-time data flows, and related architectures.
• Experience in financial services data solutions, including instruments, transactions, and positions, is desirable.
• Strong collaboration and communication skills to work across internal and external teams.

Preferred Qualifications

• Experience in the asset management and investment data domain, including multi-asset platforms and related data ecosystems.
• Understanding of asset management concepts and familiarity with various financial instruments and products.
• Industry certifications in Snowflake, dbt, cloud data engineering, data warehousing, or financial markets are highly valued.
• Interest in emerging AI technologies and how AI-driven tools can enhance engineering workflows, data quality, and analytics.
• Familiarity with AI-assisted development, automation, or data engineering best practices to boost productivity.