Data Analyst (SQL and Collibra)

Title: Business Systems Analyst (SQL and Collibra)

Location: Westlake, TX or Merrimack, NH or Smithfield, RI (Local only)

Job Description 

Must haves: Open to more junior level as long as they have: Strong SQL Experience with Collibra Analyst who can dive into detail excel files, drive process, see big picture Able to dive into data Effective communicator Project management fundamentals Nice to haves Financial or FinTech domain Understands personally identifying information

The Role
Are you an experienced business and data analyst passionate about empowering clients with innovative event and data solutions? Do you thrive in a collaborative environment that offers endless opportunities to learn, grow, and innovate? If so, a career with the Application and Platform Enabler team in Enterprise Technology could be the perfect fit for you!
Our team within Fidelity’s Enterprise Technology organization is seeking a Senior Business Analyst to drive the enablement of large-scale, event-driven platforms and services. In this role, you will leverage a blend of business, data, and technology expertise to help clients integrate messaging and streaming solutions. This position plays a vital role in delivering Fidelity’s commitment to creating exceptional customer experiences in financial services.
The Experience You Have

• 3–5+ years in Business/Data Analysis, Data Governance, or Platform Enablement roles.
• Hands-on experience onboarding teams to data/streaming platforms (e.g., Kafka) or messaging systems (e.g., Artemis or equivalent).
• Proven track record reviewing solution architectures and integration patterns for data quality, security, and compliance risks.
• Experience facilitating data governance processes (metadata, lineage, classification, stewardship, retention, and access controls).
• Background working with cross-functional teams (platform engineering, security, architecture, and product).
• Familiarity with regulated environments and enterprise data standards (e.g., SOX, HIPAA, PCI, GDPR, CCPA—depending on context).
• Experience using AI/ML tools to automate or enhance data governance activities (e.g., policy mapping, metadata extraction, anomaly detection).
• Exposure to event-driven architectures, pub/sub design, and schema management (e.g., Confluent Schema Registry or equivalent).
• Experience building or maintaining documentation, workflows, and playbooks for platform onboarding and governance reviews.

The Skills You Bring

• Architecture & Pattern Analysis: Ability to interpret solution diagrams, sequence flows, and integration designs; spot gaps, anti-patterns, and noncompliance early.
• Data Governance & Risk: Strong grasp of data classification, lineage, ownership/stewardship, access provisioning, retention, encryption, and audit requirements.
• Kafka & Artemis Fundamentals: Understanding of topics/queues, producers/consumers, partitions, DLQs, schema evolution, and message durability and security.
• AI for Governance: Proficiency using AI to accelerate governance tasks—summarizing designs, generating control checklists, mapping metadata, and surfacing anomalies.
• Process Design & Enablement: Build repeatable intake processes, readiness checklists, and decision logs that scale across teams.
• Stakeholder Management: Translate technical constraints into business risk, align with platform standards, and drive clear decisions.
• Data Analysis & Validation: Use SQL and data profiling tools to verify data quality, schema compatibility, and downstream impacts.
• Documentation Excellence: Create crisp artifacts—architecture review notes, governance assessments, onboarding guides, and FAQs.
• Tooling & Platforms: Comfortable with Jira/Azure DevOps, Confluence/SharePoint, data catalog/lineage tools, and CI/CD-adjacent workflows for governance.
• Communication & Facilitation: Lead design reviews, run working sessions, and coach teams through remediation with an enablement mindset.

The Value You Deliver

• Faster, Safer Onboarding: Shorten time-to-platform for Kafka/Artemis by front-loading governance and architecture diligence, reducing rework.
• Risk Reduction at Scale: Catch design and data compliance issues early, preventing downstream incidents, audit findings, and costly retrofits.
• Governance That Enables Delivery: Turn standards into actionable, right-sized checklists and templates—balancing control with speed.
• AI-Accelerated Reviews: Apply AI thoughtfully to triage requests, summarize architectures, and surface governance gaps—boosting throughput and consistency.
• Operational Clarity: Establish transparent intake paths, readiness criteria, and decision records so teams know exactly what “good” looks like.
• Quality & Consistency: Improve data integrity and schema lifecycle hygiene across teams, strengthening reliability of event-driven solutions.
• Cross-Team Alignment: Bridge platform, security, architecture, and product—ensuring designs are feasible, compliant, and value-driven.
• Reusable Playbooks: Create repeatable artifacts that scale—reducing onboarding friction and enabling self-service where appropriate.