Senior Data Engineer

SDL Search Partners•Boston, MA

8d•Hybrid

About The Position

This role focuses on creating business advantage from data, rather than just moving it. The client is building a modern cloud-based data platform to power analytics, reporting, investment insights, and business decision-making within a financial organization. They are seeking a Senior Data Engineer with strong technical expertise and an AI-first mindset to help build the next generation of intelligent data products and platforms. This position offers the chance to collaborate directly with investment professionals, business leaders, and technology teams, influencing how AI, automation, and modern data engineering practices transform operations. Responsibilities include designing scalable data systems, modernizing infrastructure, improving data quality, and utilizing emerging AI technologies to enhance engineering productivity and business outcomes. It's an opportunity for experienced data engineers to move beyond pipeline maintenance, influence architecture, partner with decision-makers, and foster an AI-enabled engineering culture.

Requirements

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

Nice To Haves

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.

Responsibilities

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.