Job Description

Position Summary: We are seeking a Technical Data Business Analyst (BA) to support our Enterprise Data Platform (EDP) initiatives. This role is responsible for requirement elicitation, solution analysis, process documentation, and collaboration with engineering teams to drive the successful delivery of data platform features. The ideal candidate will have a strong understanding of data ingestion, transformation, quality, and provisioning, working closely with engineering, QA, and product teams in an Agile environment to ensure high-quality product releases. This role is internal-facing and focused on bridging the gap between business needs and technical implementation, ensuring alignment with data architecture principles and product strategy. Key Responsibilities: 1. Requirements Gathering & Analysis Collaborate with engineering teams, data architects, and product owners to gather, document, and analyze functional and technical requirements for the data platform. Conduct requirement elicitation workshops, stakeholder interviews, and gap analysis to refine business and system needs. Define and document functional and non-functional requirements for data platform components, including data ingestion, quality, mapping, transformation, and provisioning. Analyze and translate business needs into Epics, User Stories, and Acceptance Criteria in JIRA/Confluence. Identify dependencies, risks, and mitigation strategies related to product delivery and data platform development. Work closely with engineering teams to validate technical feasibility and identify potential constraints. 2. Solution Design & Techno-Functional Documentation Partner with engineering and architecture teams to define data flow diagrams, process workflows, and system integrations. Create low-fidelity wireframes, process maps, and technical documentation to support product development. Document data lineage, metadata, and transformation logic to ensure data integrity and governance. Work closely with UX teams to refine user journeys and interface requirements. Collaborate with data scientists and engineers on data modeling, API integrations, and metadata-driven architectures. 3. Agile Product Delivery & Engineering Collaboration Act as a liaison between product and engineering teams, ensuring requirements are well-defined and development efforts are aligned with business needs. Participate in Agile ceremonies (Sprint Planning, Refinement, Stand-ups, and Retrospectives), ensuring backlog items are well-structured and prioritized. Support the engineering team during sprint development, providing clarifications on requirements and resolving blockers. Perform impact analysis for new features, enhancements, and system modifications. Assist in test data preparation, review of test plans, and validation of developed features. Coordinate with QA to ensure proper SIT, UAT, and regression testing for each release cycle. 4. Post-Release & Continuous Improvement Monitor product performance and collect feedback from engineering teams, business users, and stakeholders for continuous improvements. Assist in triaging production defects, analyzing root causes, and identifying workarounds with engineering teams. Document and track key performance metrics (KPIs) and operational insights related to data platform usage and adoption. Drive process improvements in requirement management, backlog grooming, and release planning. Qualifications: Must-Have: 5-8 years of experience as a Technical Business Analyst, with a strong focus on data platforms, data engineering, or data-driven product development. Experience with data ingestion, transformation, quality, and provisioning in large-scale enterprise environments. Strong knowledge of SQL, data modeling, ETL processes, and metadata-driven architectures. Expertise in Agile/Scrum methodologies, backlog management, and sprint planning. Hands-on experience with JIRA, Confluence, and process mapping tools. Ability to create process diagrams, data flow diagrams, wireframes, and solution documentation. Experience collaborating with engineering teams on technical requirements and solution validation. Strong analytical and problem-solving skills, with the ability to bridge business and technical perspectives. Excellent communication skills, with experience engaging both technical and non-technical stakeholders. Preferred Qualifications: Experience working in Clinical SaaS Platforms or GxP validated systems. Exposure to AI-driven data platforms and solutions. Knowledge of metadata-driven data warehousing architectures. Hands-on experience with Python, R, or data analytics tools We also offer: o Group Health Insurance covering family of 4 o Term Insurance and Accident Insurance o Paid Holidays & Earned Leaves o Paid Parental LeaveoLearning & Career Development o Employee Wellness