Sr. Data Engineer

6-12+ month contract at $60-80/hour (W2) based on experience. Hybrid onsite in Boston, MA – 3 days/week onsite. Must be local.

About the role

The Lead Data Engineer contributes to a long-term strategic initiative to unify and harmonize our investment data. This initiative enables enhanced investment decision making, risk management, and client reporting for our multi-asset platform by delivering consistent, timely, accurate, and user-friendly data to investors, risk teams, and clients. The Investment Data Management Office is actively searching for a Lead Data Engineer to implement data engineering and analytics solutions.

Responsibilities

• Develop and maintain data models in dbt (Data Build Tool) within Snowflake, implementing business logic and ensuring alignment with existing architecture and data standards.
• Manage and contribute to dbt projects, ensuring code quality, proper documentation, and alignment with 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 and participate in all development activities, develop and implement solutions to meet business requirements that align with program strategic objectives.
• Drive continuous improvement of data quality, resiliency, control, efficiency, and monitoring.
• Troubleshoot complex system interactions to find the root cause of problems.
• Partner with platform lead to design, develop, implement, and deploy new software components to the investment data platform.
• Partner with data architect to evaluate and finalize the unified data model.
• Partner with integration architect to upgrade and integrate data ingestion and data delivery tools with the unified data platform.
• Upgrade and integrate transformation tools, data validation tools, and orchestration tools with the unified data platform to implement data engineering, analytical engineering, and data maintenance capabilities.
• Provide support during unexpected outages.

Requirements

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

Preferred Qualifications

• Experience working 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/investment operations are highly valued.
• Demonstrated interest in emerging AI technologies and an understanding of how AI-driven tools can improve day-to-day 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.

Pay

$60-80/hour (W2) depending on experience.

Schedule

Hybrid onsite in Boston, MA – 3 days/week onsite.