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Business Analyst – Data Integration

Alpharetta, GA

12+ months Contract - Onsite

Role Overview

We are seeking an experienced Business Analyst – Data Integration to join our growing Technology & Data team. In this role, you will serve as the critical bridge between business stakeholders and engineering teams, driving the design, documentation, and delivery of enterprise-grade data integration initiatives. You will own the end-to-end lifecycle of API-based and ETL integration projects — from identifying data elements and metadata, to creating source-to-target mapping documents and data dictionaries — ensuring that private markets data flows accurately, reliably, and performantly across our platform.

Key Responsibilities

Data Integration & API Projects

• Lead business analysis for data integration (API and ETL) projects, gathering and translating complex business requirements into actionable technical specifications.
• Identify, catalog, and validate data elements and metadata across source and target systems to create comprehensive source-to-target mapping documents.
• Build and maintain data dictionaries that define data fields, formats, lineage, and business rules across private markets data ecosystem.
• Collaborate with engineering and data engineering teams to design integration workflows that connect investor, shareholder, company, and transaction data domains.
• Partner with third-party data vendors and internal product teams to define API contracts, payload structures, and data exchange standards.

Enterprise Data Modeling

• Contribute to the design and governance of enterprise data model, ensuring consistency across investor records, cap table data, fund structures, and private placement transactions.
• Develop logical and physical data models in alignment with business requirements and downstream reporting needs.
• Review and validate data model changes with architects and senior engineers, ensuring referential integrity and scalability.
• Maintain model documentation and facilitate data model reviews across cross-functional stakeholders.

Troubleshooting, Performance Tuning & Monitoring

• Diagnose and resolve data pipeline failures, data quality issues, and integration anomalies across staging, UAT, and production environments.
• Use database tools (e.g., SQL, Snowflake, dbt, Datadog, Grafana, or similar) to monitor pipeline health, job execution times, and data freshness SLAs.
• Conduct performance tuning analysis on slow-running queries, inefficient joins, and poorly indexed tables — producing optimization recommendations backed by profiling data.
• Set up and refine alerting thresholds for data pipelines to enable proactive issue detection and minimize downstream business impact.
• Produce root cause analysis (RCA) reports following incidents and drive post-mortem remediation actions.

Stakeholder Collaboration & Documentation

• Work cross-functionally with Deal Operations, Research, Product, Legal, and Compliance teams to identify use cases, data requirements, and functional specifications.
• Facilitate requirements workshops, data discovery sessions, and sign-off reviews with business stakeholders at all levels.
• Author and maintain integration runbooks, BRDs (Business Requirements Documents), functional specifications, and test plans.
• Support UAT by defining acceptance criteria, coordinating test data preparation, and tracking defect resolution.
• Communicate integration progress, risks, and blockers clearly to engineering leads and business sponsors.

Required Qualifications

• 5–8 years of experience as a Business Analyst with a strong focus on data integration, ETL, or API-based projects in a FinTech, financial services, or enterprise data environment.
• Hands-on experience creating source-to-target mapping documents and data dictionaries for complex, multi-source integration projects.
• Solid understanding of enterprise data modeling concepts (logical/physical models, ERDs, normalization, dimensional modeling).
• Proficiency in SQL for data querying, profiling, and validation across relational and cloud-based data platforms (e.g., Snowflake, PostgreSQL, Redshift).
• Experience with API integration projects — including REST/JSON payload analysis, Swagger/OpenAPI documentation, and endpoint mapping.
• Demonstrated experience in performance tuning and troubleshooting data pipelines or integration jobs.
• Familiarity with data monitoring tools (Datadog, Monte Carlo, Great Expectations, or equivalent) and alerting frameworks.
• Experience working in Agile/Scrum environments with tools such as Jira and Confluence.
• Strong documentation skills with the ability to produce clear, audience-appropriate technical and business-facing artifacts.
• Bachelor''s degree in Computer Science, Information Systems, Finance, or a related quantitative field.

Preferred Qualifications

• Experience in FinTech, private equity, capital markets, or investment platforms (familiarity with cap tables, private placements, or fund structures is a strong plus).
• Exposure to dbt, Airflow, Fivetran, or other modern data stack tooling.
• Knowledge of data governance frameworks and data catalog tools (e.g., Alation, Collibra, Atlan).
• Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure in a data engineering context.
• CBAP, PMI-PBA, or equivalent business analysis certification.
• Familiarity with SDLC governance and change management practices in a regulated financial environment.

Thanks and regards,

Asha Krishna

Associate Director - Talent Partner - US & Canada

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