Senior Data Engineer

Build the Future of AI-Enabled Data Platforms

Hybrid | Boston Area | Strong Compensation (Base + Bonus + Profit Sharing)

Applicants must be authorized to work in the U.S. without current or future visa sponsorship

Most data engineering roles focus on moving data. This one focuses on creating business advantage from it.

Our client is building a modern cloud-based data platform that powers analytics, reporting, investment insights, and business decision-making across a sophisticated financial organization. They are looking for a Senior Data Engineer who combines strong technical expertise with an AI-first mindset to help build the next generation of intelligent data products and platforms.

This is an opportunity to work directly with investment professionals, business leaders, and technology teams while helping shape how artificial intelligence, automation, and modern data engineering practices transform the way the organization operates.

You'll help design scalable data systems, modernize infrastructure, improve data quality, and leverage emerging AI technologies to accelerate both engineering productivity and business outcomes.

For experienced data engineers looking to move beyond simply maintaining pipelines, this role offers the chance to influence architecture, partner directly with decision-makers, and help build an AI-enabled engineering culture from the ground up.

Why Top Candidates Are Interested

Work at the Intersection of AI and Data Engineering - Leverage modern AI development tools and emerging technologies as part of your everyday engineering workflow while helping shape how a high-performing team adopts AI responsibly and effectively.

Direct Business Impact - Partner closely with investment professionals, analysts, and business leaders to build systems that support critical decisions and drive measurable organizational value.

Modern Technology Stack - Work with leading technologies including Snowflake, dbt, Python, Terraform, cloud infrastructure platforms, workflow orchestration tools, and modern AI-assisted development environments.

Influence Architecture and Standards - Play a key role in defining engineering best practices, data modeling standards, governance processes, and platform strategy as the organization continues to scale.

Accelerated Professional Growth - Gain exposure to business operations, financial markets, cloud-native architectures, AI innovation, and enterprise-scale data platforms while working alongside experienced technical and business leaders.

Meaningful Compensation - Competitive compensation package including base salary, performance bonus, and profit-sharing opportunities.

What You'll Do

• Design and build scalable data platforms, pipelines, and analytics solutions that support enterprise reporting and decision-making.

• Develop and maintain modern data models that enable reliable, high-quality analytics across the organization.

• Build, test, and deploy data products using technologies such as Snowflake, dbt, Python, and cloud-native tooling.

• Leverage AI-powered engineering tools to accelerate development, improve quality, and increase overall team productivity.

• Implement data governance, lineage, observability, and quality controls to ensure trust in business-critical data.

• Partner directly with business stakeholders to translate complex requirements into sustainable technical solutions.

• Evaluate and implement emerging technologies that improve engineering effectiveness and platform capabilities.

• Contribute to architecture reviews, technical standards, and engineering best practices.

• Mentor and collaborate with fellow engineers while helping raise the overall technical bar of the organization.

• Support the ongoing evolution of an AI-enabled engineering culture focused on innovation, quality, and continuous improvement.

What We're Looking For

We are particularly interested in candidates who pair strong engineering fundamentals with intellectual curiosity and a passion for leveraging modern AI capabilities to build better systems.

Ideal candidates will offer:

• 5+ years of experience in data engineering, software engineering, analytics engineering, or a related technical discipline.

• Hands-on experience building and supporting cloud-based data platforms and modern analytics ecosystems.

• Strong expertise in SQL, Python, and data engineering best practices.

• Experience with Snowflake, dbt, data warehousing, dimensional modeling, and modern data transformation frameworks.

• Familiarity with infrastructure-as-code, cloud platforms, CI/CD practices, and automated deployment methodologies.

• Practical experience using AI-powered development tools such as ChatGPT, Claude, Cursor, Copilot, Codex, or similar technologies.

• A strong understanding of data quality, governance, testing, observability, and scalable system design.

• Excellent communication skills with the ability to collaborate across technical and non-technical teams.

• Strong problem-solving capabilities, sound engineering judgment, and the ability to operate effectively in ambiguous environments.

• A builder's mindset with a passion for continuous learning, innovation, and delivering measurable business impact.

Preferred Experience

• Asset management, financial services, investment management, credit, or capital markets environments.

• AI-powered internal tools, LLM applications, retrieval systems, agents, or workflow automation technologies.

• Airflow, Dagster, or similar orchestration platforms.

• Business intelligence and reporting tools such as Power BI.

• Data governance, lineage, cataloging, and observability solutions.

• Real-time or streaming data architectures.

• Mentoring engineers and contributing to technical leadership initiatives.