Data Engineer

• Design, build, and maintain scalable data pipelines across internal databases, vendor systems, and our data warehouse
• Support both batch and event-driven or CDC-based data workflows
• Improve pipeline reliability, observability, and performance
• Troubleshoot issues in production and proactively solve data quality or system problems
• Build and maintain data warehouse schemas and transformation layers to support analytics and operational use cases
• Communicate clearly about implementation choices, tradeoffs, and technical constraints
• Identify opportunities to improve data workflows through better tooling, automation, and engineering practices
• Help shape scalable patterns for how data is ingested, transformed, stored, and accessed

Senior Data Engineer

• Develop advanced data engineering solutions that power critical investment decisions
• Design robust data models and ETL pipelines
• Apply modern DevOps and Agile practices

• Perform applications database administration (Oracle and Snowflake) services including SQL code review, performance analysis, query tuning, database application design, physical data modeling, development support and Engineering.
• Proactively monitor databases servers and respond to any alerts
• Provide database support in all phases of SDLC and agile experience is preferred
• Participate in 24X7 on call rotation schedule for various production support, database maintenance, housekeeping and installs
• Work with enterprise teams for Systems Administrators, Cyber Security and Capacity Planning groups as and when situation demands
• Ability to quickly diagnose the problem areas and come up with solutions and/or workarounds
• Should have strong time management skills with willingness and ability to prioritize multiple projects/initiatives at the same time
• Establish database standards for operations, upgrades, migrations and onboarding new applications and/or clients
• Write clear, concise, well organized user documentation to maintain standards and procedures

Senior Data Engineer – Oracle RAC DBA

• lead a team of data architects in the Asset Management Technology’s architecture team
• set the architectural direction for AI-ready platforms
• establish governance frameworks that enable consistent excellence
• build and develop high-performing data architecture teams
• architect and deliver high-impact solutions
• design and optimize enterprise-scale data platforms
• establish reference architectures and accelerators
• lead technical deep dives and design reviews

Vice President, Data Architecture

• Drive the Data Architecture and Data platform modernization for the Workplace Investing division
• Work with Enterprise Architects to modernize legacy systems
• Collaborate closely with business partners and technology teams

Director, AI/ML, Data Architecture

• Collaborate with other Engineers and Architects to define the enterprise data architecture roadmap.
• Drive the design and optimization of OLTP and OLAP models for scalability, performance, and maintainability.
• Establish standards for data modeling, storage, and integration across systems.
• Partner with other key stakeholders within engineering in developing a comprehensive data and BI strategy aligned with business objectives.
• Define data governance practices, data access control, compliance, and quality standards.
• Lead proof-of-concepts (POCs) for new data technologies and frameworks.
• Own the architectural review process and guidance to development teams on data-related projects.
• Establish and ensure best patterns and practices for ORM usage (Entity Framework and others) and SQL optimization, according to business needs.
• Evaluate and recommend where AI/ML can enhance data-driven decision-making.
• Stay current with modern data engineering trends, cloud-native architectures, and big data platforms.
• Actively participate and take ownership of Data Architecture artifacts via ADR process.
• Drive AI adoption by introducing and guiding teams in leveraging AI capabilities within the data engineering space to enhance internal efficiency, innovation, and decision-making in everyday workflows.
• Liaison between technology and product teams assisting teams in translating business requirements into tangible architectures that meet business needs now in and in the future.
• Design data architectures that accurately reflect and support evolving complex product and business processes and are required by our customer base.
• Lead data architecture initiatives, collaborating with cross functional teams, from concept through implementation, including governance and quality frameworks.
• Identify opportunities for predictive analytics and advanced modeling.
• Support and promote the company values through positive interactions with both internal and external stakeholders on a regular basis.
• Other strategic business initiatives or special cross-functional project involvement as required.

Data Architect

• Lead a distributed engineering team across platform/product engineering, connectors, QA, DevOps/infra, AI implementation, data governance, and support.
• Own delivery, quality, release discipline, and execution of the technical roadmap.
• Install engineering discipline where it's thin: automated testing, QA, CI/CD, release governance, and versioning.
• Drive repeatable, perimeter-safe deployments, including containerization, infrastructure-as-code, secure deployment, and SOC 2 readiness.
• Partner with the Chief Architect on the connector framework, canonical metadata model, architecture decisions, and product IP.
• Build the team: assess current talent, retain the strong, hire the gaps, and align the team plan to the roadmap.
• Push practical AI use across coding, review, testing, ops, and engineering productivity.

Director of Engineering – Data Platform

• Lead the design and evolution of Foley’s enterprise data architecture
• Contribute to the ongoing development of our Enterprise Data Model
• Define standards and best practices for data modeling, storage, access, and reliability
• Drive architectural decisions that balance scalability, maintainability, and performance
• Design, build, and maintain scalable data pipelines across internal systems, vendor platforms, and the data warehouse
• Improve data quality, observability, and reliability across core workflows
• Optimize data workflows for efficiency and long-term operational health
• Support both batch and event-driven or CDC-based pipeline patterns
• Own schema design and warehouse modeling strategy, including dimensional and normalized approaches where appropriate
• Help define and implement data governance best practices, including RBAC
• Ensure shared definitions, documentation, and trust in core business data
• Serve as a thought partner to Engineering, Product, Analytics, and business teams
• Translate technical complexity into clear recommendations and tradeoffs
• Raise the bar for data engineering practices across the organization
• Help the company make better decisions through strong, accessible data foundations
• Identify opportunities to improve workflows through automation, tooling, and thoughtful use of AI
• Experiment pragmatically with new technologies and scale what works
• Build systems and guardrails that enable teams to move faster without sacrificing quality

Staff Data Engineer

• lead the dataset onboarding efforts for the Quantitative Research Platform (QRP) team
• collaborate with technology partners to integrate financial and alternative datasets into QRP
• work closely with researchers to design data consumption patterns
• partner with Data Operations to maintain data quality

Director, Quant Data Platform

• Lead the design and delivery of database engineering solutions
• Perform applications database administration services including SQL code review, performance analysis, and database application design
• Establish database standards for operations, upgrades, migrations and onboarding new applications
• Interface with enterprise teams for Systems Administrators, Cyber Security and Capacity Planning groups
• Write clear, concise, well organized technical documentation to maintain standards and procedures

Principal Data Engineer

• Serves as a lead in the analysis of business requirements associated with the design and implementation of highly complex, highly scalable enterprise data processes
• Designs and develops robust and efficient processes for extracting, loading and transforming data to meet the needs of enterprise scale projects
• Provides guidance and participates in activities involved in the analysis, design, development, troubleshooting, debugging and maintenance of an enterprise data management and data ecosystem
• Identifies, investigates, tracks, and resolves the most complex technical errors ensuring the solution is timely and of acceptable quality
• Establishes and enforces database standards, guidelines, procedures and quality assurance for database deliverables such as conceptual design, logical data model capacity planning, external data interface specs, data loading, data maintenance plan and security
• Reviews and analyzes data objects and models to improve data management and data access
• Designs, constructs, tests and implements extraction and transformation programs, processes and cycles for historical and current source data
• Creates technical specification for supporting enterprise data transformation processes and supplementing system documentation for ETL processes
• Performs data profiling, source-target mappings, data transformation development, optimization, testing and implementation
• This position participates and serves as a lead in maintaining the ETL environment for the company’s system-wide enterprise data warehouse.

Data Engineer jobs in New Hampshire

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Senior Data Engineer

Senior Data Engineer

Senior Data Engineer – Oracle RAC DBA

Vice President, Data Architecture

Director, AI/ML, Data Architecture

Data Architect

Director of Engineering – Data Platform

Staff Data Engineer

Director, Quant Data Platform

Principal Data Engineer

Supply Chain Data Engineer