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About the Role
Baker Tilly is seeking a Sr Data Engineer to join the founding team of the firm's AI Product Group (APG). This hands-on engineering role is responsible for building scalable, secure, and reliable data infrastructure that powers the firm's AI applications and intelligent agents. The position focuses on developing a governed data foundation and building the knowledge layer for AI agents.
Responsibilities
- Design and Build Data Pipelines: Develop, implement, and maintain scalable batch and incremental data pipelines that transform structured and unstructured information into clean, validated, business-ready datasets within a modern lakehouse environment.
- Develop and Maintain Lakehouse Architecture: Build and optimize data processing and transformation layers using modern lakehouse principles, including medallion architecture, data modeling, and integration of enterprise and legacy data sources.
- Ensure Data Quality, Lineage, and Provenance: Implement automated validation, reconciliation, lineage tracking, and metadata management to ensure data accuracy, consistency, traceability, and reliability throughout the data lifecycle.
- Build Data Models and Identity Resolution Capabilities: Develop scalable data models, data contracts, and entity-resolution processes that establish consistent client, engagement, and document identities across enterprise data sources.
- Implement Data Governance and Access Controls: Support data cataloging, classification, permissions, and access management to ensure sensitive information is appropriately governed and accessible only to authorized users and AI agents.
- Develop Knowledge Graph and Retrieval Capabilities: Build and maintain knowledge graph structures, data relationships, search indexes, and retrieval pipelines that enable AI applications to access relevant, accurate, and properly governed enterprise information.
- Support AI Data Readiness and Continuous Learning: Develop pipelines that capture AI agent activity, practitioner feedback, reviews, and corrections to support ground-truth datasets, AI evaluation, and ongoing improvements in data and retrieval quality.
- Drive Evaluation-Based Data Engineering: Establish measurable quality standards, testing frameworks, benchmarks, and validation processes to assess data extraction, retrieval effectiveness, and grounding accuracy.
- Maintain Data Freshness and Reliability: Implement incremental processing, change data capture, versioning, and monitoring capabilities to ensure data products, knowledge graphs, and search indexes remain accurate and current as source systems evolve.
- Own Production Delivery and Operational Support: Deploy, monitor, troubleshoot, and maintain production data pipelines, applying strong engineering practices, automated testing, code reviews, and operational documentation.
- Support Knowledge Transfer and Technical Ownership: Collaborate with external engineering partners to transition data solutions into internally owned, documented, and maintainable production environments, including the development of reusable code, tests, and runbooks.
- Collaborate Across Global and Cross-Functional Teams: Partner with AI Engineering, Platform & Production Engineering, enterprise data teams, subject matter experts, and engineering teams in India to align technical solutions with enterprise standards and business objectives.
- Support Strategic Initiatives: Participate in special projects and perform other duties as assigned to advance the firm's AI and data platform capabilities.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred.
- 3 years of hands-on data engineering or software engineering experience, including demonstrated success developing, deploying, and maintaining production data pipelines.
- Required experience independently building and operating production pipelines on a modern lakehouse platform, with demonstrated ownership of data processing, transformation, and operational reliability.
- Required experience implementing data quality, lineage, or data contracts within production pipelines, including automated testing, reconciliation, validation, or traceability practices.
- Strong proficiency in Python and SQL, with demonstrated ability to develop, optimize, test, and maintain production-quality data engineering solutions.
- Strong understanding of data modeling principles, including the ability to design scalable, maintainable data structures that accommodate evolving business requirements and source systems.
- Experience designing and developing batch and incremental data pipelines for structured and unstructured enterprise data.
- Strong software engineering fundamentals, including version control, automated testing, code reviews, debugging, and development of reliable, repeatable data processing workflows.
- Demonstrated ability to validate technical solutions through measurable outcomes, including automated tests, benchmarks, experiments, performance metrics, or comparative evaluations.
- Experience with modern lakehouse technologies such as Databricks, Apache Spark, Delta Lake, or medallion architecture strongly preferred.
- Experience with cloud-based data platforms, preferably Microsoft Azure, and associated data storage, processing, and integration services preferred.
- Familiarity with enterprise data governance capabilities, including data catalogs, classification, access controls, lineage, and technologies such as Unity Catalog or comparable solutions preferred.
- Experience with knowledge graphs, graph databases, graph data modeling, vector search, hybrid search, or retrieval-based applications preferred.
- Familiarity with unstructured data processing, document extraction, metadata management, content chunking, or search indexing preferred.
- Experience with entity resolution, master data management, change data capture, or incremental data processing preferred.
- Understanding of data provenance, traceability, and governance requirements within complex enterprise or regulated environments.
- Strong analytical thinking, technical judgment, and problem-solving skills, with the ability to independently evaluate trade-offs, troubleshoot complex issues, and develop scalable solutions.
- Excellent written and verbal communication skills, including the ability to document technical solutions, explain complex concepts, and collaborate effectively with technical and nontechnical stakeholders.
- Demonstrated ability to work with business subject matter experts, engineering teams, and globally distributed stakeholders to translate requirements into reliable data solutions.
- Ability to manage competing priorities, adapt quickly to evolving requirements, and deliver high-quality solutions in a fast-paced, collaborative environment.
- Experience using AI-assisted and agentic development tools to improve engineering productivity, or a strong willingness to incorporate these technologies into daily development practices.
- Prior experience with AI, machine learning, LLM systems, or knowledge graphs is not required; demonstrated engineering fundamentals and the ability to learn emerging technologies are essential.
- No professional certifications or licenses required.
Skills
- Python
- SQL
- Data Modeling
- Batch Data Pipelines
- Incremental Data Pipelines
- Lakehouse Architecture
- Medallion Architecture
- Data Quality
- Data Lineage
- Data Provenance
- Metadata Management
- Data Governance
- Access Controls
- Knowledge Graphs
- Retrieval Pipelines
- AI Data Readiness
- Evaluation-Based Data Engineering
- Data Freshness
- Reliability
- Production Delivery
- Operational Support
- Automated Testing
- Code Reviews
- Knowledge Transfer
- Technical Ownership
- Collaboration
- AI-assisted development tools
- Agentic development tools
Location
- Remote
- Onsite
- Hybrid
Work Type
- Full-time
Experience Level
- Senior
- 3 years of hands-on data engineering or software engineering experience
Education Level
- Bachelor's degree in Computer Science, Engineering, or a related field
- Advanced degree preferred
Salary/Compensations
- $185,000 – $230,000
Benefits
- Comprehensive compensation and benefits package
About the Company
- Baker Tilly is a leading advisory, tax and assurance firm, providing clients with a genuine coast-to-coast and global advantage in major regions of the U.S. and in many of the world’s leading financial centers.
- Baker Tilly Advisory Group, LP and Baker Tilly US, LLP (Baker Tilly) provide professional services through an alternative practice structure in accordance with the AICPA Code of Professional Conduct and applicable laws, regulations and professional standards.
- Baker Tilly US, LLP is a licensed independent CPA firm that provides attest services to its clients.
- Baker Tilly Advisory Group, LP and its subsidiary entities provide tax and business advisory services to their clients.
- Baker Tilly Advisory Group, LP and its subsidiary entities are not licensed CPA firms.
- Baker Tilly Advisory Group, LP and Baker Tilly US, LLP, trading as Baker Tilly, are independent members of Baker Tilly International, a worldwide network of independent accounting and business advisory firms in 141 territories, with 43,000 professionals and a combined worldwide revenue of $5.2 billion.
- Visit bakertilly.com or join the conversation on LinkedIn, Facebook and Instagram.
Equal Opportunity
- Baker Tilly is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, gender identity, sexual orientation, or any other legally protected basis, in accordance with applicable federal, state or local law.