Data Integration Senior Engineer

Position summary

The Data Integration Senior Engineer serves as Strategic Intelligence's hands-on technical lead for data platform engineering, DataOps, and enterprise data integration. The role turns governed data capabilities—including master data, entity resolution, semantic models and layers, knowledge graphs, and reusable data products— into secure, production-grade pipelines, APIs, event flows, services, and controlled interfaces that support analytics, automation, AI, and agent-enabled use cases.

The role owns the runtime engineering lifecycle for these capabilities, including integration design, release engineering, deployment automation, environment promotion, observability, incident response, reliability, recoverability, performance, and cost efficiency. The Senior Engineer establishes reusable engineering patterns and replaces brittle point-to-point integrations, manual handoffs, duplicate data stores, and one-off extracts with governed, scalable, and supportable services and delivery mechanisms.

The role operates within established business, data governance, product, analytical, architecture, security, and platform ownership boundaries. Relevant capability and domain owners retain accountability for business meaning, taxonomy and ontology standards, stewardship, data-quality policy, master-data requirements, analytical methods, product priorities, and business outcomes. This role owns the technical integration, release engineering, and production operation of approved data capabilities. Finance-domain analysis, measures, and products are outside this role's remit.

Job duties and responsibilities

• Serve as the hands-on technical lead for data platform engineering, DataOps, and enterprise integration, contributing directly to architecture, coding, testing, deployment, troubleshooting, and production support.
• Co-design end-to-end solutions with relevant capability owners across business, data, product, architecture, security, and technology, defining integration boundaries, non-functional requirements, release plans, acceptance criteria, and support models from the outset.
• Develop and operate production-grade batch, near-real-time, and event-driven pipelines, APIs, services, and controlled interfaces connecting approved internal systems, external data sources, enterprise platforms, and downstream consumers.
• Create reusable connectors and integration patterns that support analytics, automation, AI, and agent-enabled use cases while minimizing point-to-point dependencies and duplicated logic.
• Establish and enforce engineering standards for source control, code review, CI/CD, automated testing, documentation, secrets management, environment promotion, release and rollback, recovery, and operational support.
• Define and monitor service levels and non-functional requirements for availability, freshness, latency, throughput, recoverability, security, and cost, with clear runbooks and ownership for production support.
• Automate deployment, monitoring, alerting, logging, and observability for data services and integrations; make metadata, lineage, transformation logic, quality results, assumptions, and limitations transparent and discoverable.
• Diagnose incidents and data-delivery failures, perform root-cause analysis, remediate defects, and improve reliability, performance, recoverability, and cost efficiency across pipelines, APIs, integrations, and platform services.
• Productionize MDM, entity-resolution, semantic-layer, knowledge-graph, and governed data-product capabilities while preserving approved data contracts, versioning, access controls, quality rules, and traceability.
• Manage schema, interface, and data-contract evolution, including impact assessment, backward compatibility, consumer communication, and coordinated deprecation of legacy interfaces.
• Refactor or retire brittle integrations, manual handoffs, duplicate data stores, and one-off extracts in favor of reusable, governed, and supportable services that reduce operational risk and technical debt.
• Partner with the functions responsible for enterprise architecture, platform engineering, information security, privacy, records management, and application ownership to align solutions with architecture, access-control, platform, and compliance standards and to surface capability gaps.
• Work with the capabilities responsible for master data, entity resolution, semantic modeling, knowledge graphs, and governed data products throughout design, testing, release, and support. This role owns deployment and runtime reliability; the appropriate functional owners remain accountable for the correctness and evolution of underlying rules, models, definitions, and data-product logic.
• Partner with product and portfolio stakeholders on feasibility, dependencies, effort, risk, sequencing, and build-buy-partner decisions; portfolio prioritization, product lifecycle, adoption, and value realization remain with the appropriate product and business owners.
• Partner with analytics, reporting, automation, AI, and other approved consumers to deliver governed data through production interfaces, while the appropriate domain owners retain analytical methods, measures, application configuration, interpretation, and outcomes.
• Manage technical vendors, contractors, and implementation partners; contribute to platform capacity planning, cost management, performance optimization, and tool evaluation; and ensure engineering quality, documentation, supportability, and knowledge transfer.
• Perform other duties as assigned.

Job duties and responsibilities included are not exhaustive and may be supplemented asnecessary.  Reed Smith reserves the right to revise or modify job duties and responsibilities at any time. 

Requirements

Education: Bachelor's degree in computer science, data engineering, information systems, or a related field. Master's degree preferred.

Experience: 

• Minimum 7 years of experience in data engineering, integration engineering, data platform engineering, or enterprise data management, including hands-on technical leadership in a complex organization.
• Demonstrated experience architecting, building, deploying, and operating production data pipelines, APIs, and integrations on a modern cloud data platform such as Snowflake or a comparable platform.
• Experience establishing engineering standards and production practices for automated testing, release management, secrets management, observability, incident response, root-cause analysis, recovery, and operational support.
• Experience managing schema and interface evolution, data contracts, metadata, lineage, and backward compatibility across producers and consumers.
• Experience deploying and operating MDM, semantic, knowledge-graph, or reusable data-product services in production environments strongly preferred.
• Experience working within enterprise architecture, security, privacy, records-management, access-control, and platform requirements and partnering effectively with application and infrastructure teams.
• Experience managing technical vendors, contractors, or implementation partners and ensuring sustainable knowledge transfer; experience in professional services, legal, or another complex, matrixed environment preferred.

Skills: 

• Hands-on engineering leadership with the ability to move from architecture and design to code, testing, deployment, production troubleshooting, and operational support.
• Strong hands-on SQL skills and experience with a programming language such as Python, together with orchestration, transformation, API and event-integration, version-control, and CI/CD tooling.
• Strong systems thinking across source applications, data models, integration patterns, platforms, security controls, and downstream consumption, with the ability to identify root causes and make pragmatic trade-offs across quality, speed, cost, risk, and maintainability.
• Ability to design modular, reusable, secure, observable, and scalable pipelines, APIs, integration services, and platform patterns rather than one-off extracts or manual handoffs.
• Strong understanding of DataOps, DevOps, CI/CD, production operations, service reliability, and platform engineering, with sufficient familiarity with MDM, semantic, and data-product concepts to deploy and operate those capabilities effectively.
• Clear written and verbal communication skills, including the ability to explain technical choices, constraints, support implications, and risks to business, data, analytics, product, and technology stakeholders.
• High degree of professionalism, discretion, sound judgment, flexibility, and adaptability in complex, dynamic, or rapidly evolving situations.

Additional information

Supervisory responsibilities:  Provides technical leadership across cross-functional delivery teams and directs external implementation partners, contractors, and project resources as applicable.

Equipment used: Personal computer and other office equipment such as telephone,  calculator, copier, scanner, etc.

Essential job functions

• Ability to sit or stand for extended periods and perform tasks requiring prolonged and/or extensive computer use.
• Ability to use computers, telecommunications, and digital collaboration tools to perform core job responsibilities.
• Ability to engage in effective and professional communication.
• Ability to analyze complex information while maintaining attention to detail, managing multiple priorities, and exercising sound judgment in decision-making.
• Ability to access, use, and safeguard confidential and sensitive information while performing job responsibilities in work environments that support confidentiality, privacy, and information security requirements.
• Ability to work extended or adjusted hours as needed, including evenings, weekends, holidays, and early start times to support collaboration with international stakeholders in EMEA and to meet business, operational, or project needs.
• Ability to travel for meetings, training and conferences as required.
• Ability to work in-office as required to meet business or project needs.

Working conditions: Works remotely. Occasionally called upon to work hours in excess of your normal daily schedule. Potential for in-office work requests as needed, so proximity to the office is important.

Pay ranges

This represents the presently anticipated low and high end of Reed Smith's pay range for this position. Actual pay may vary based on various factors, including but not limited to location and experience.

• Atlanta, Austin, Dallas, Denver, Houston, Miami, Pittsburgh: $152,000 - $172,000
• Chicago, Philadelphia, Wilmington: $163,000 - $184,000
• Princeton, Washington, D.C., Boston: $174,000 - $196,000
• New York: $191,000 - $213,000

Employee benefits overview

Our comprehensive benefits package includes:

• 401(k) Retirement Plan
• Medical Insurance
• Health Savings Account (HSA)
• Virtual Health Services
• Dental Insurance
• Vision Insurance
• Accident Insurance
• Hospital Indemnity Insurance
• Critical Illness Insurance
• Life Insurance
• Short-Term Disability Coverage
• Long-Term Disability Coverage
• Flexible Spending Accounts (FSA)
• Lyra Health Employee Assistance Program (EAP)
• Paid Family Leave (for eligible Exempt and Non-Exempt staff)
• Transportation Benefit
• Back-up Child Care Services
• College Coach Program
• Pet Insurance
• Paid Sick Time (for Exempt staff)
• Paid Time Off (available to all full-time, non-temporary employees)

Reed Smith offers a challenging work environment, business casual dress code and a total compensation package that includes a competitive salary, flexible benefits program, tuition assistance, and generous 401(k) plan.

Reed Smith is an Equal Opportunity Employer with Core Values of Integrity, Excellence, Teamwork & Respect, Innovation, and Impact. Reed Smith also provides reasonable accommodations in accordance with law, including in the application and interview process.

Qualified candidates only. No search firms.