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# Senior Data Engineer

- **Company:** SDL
- **Location:** Boston, MA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Business Analytics Applications, Data Analysis, Automated Storage and Retrieval Systems, Cloud Computing, Cloud Engineering, Continuous Integration, Information Engineering, Data Governance, Data Transformation, Data Warehousing, Cursor, Programming Tools, Dimensional Modeling, Python (Programming Language), Power BI, Software Tools, Microsoft Copilot, DataOps, Software Engineering, SQL Databases, Data Streaming, Cloud Platform System, Large Language Models, Snowflake, Build Management, Deployment Automation, Data Management, Tools for Reporting, Claude, GPT
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-boston-ma--08f9b4d3-ec85-4b08-8e33-2c74dadf4f55

## About the Role

Cloud Computing, Artificial Intelligence (AI), Investment Reporting, Automation, Data Quality, Quality Management, Systems Scalability, Emerging Technology, Programming Tools, Investment Analysis, 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.

## Description

* 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.