Lead Data Business Analyst at Referrals Only

pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

09 Jun, 26

Salary

0.0

Posted On

11 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Management, Stakeholder Management, Requirements Engineering, Data Governance, Data Integration, MDM, Business Analysis, Data Quality, Data Modeling, Technical Literacy, Product Ownership, Data Strategy, Business Intelligence, Visualization Tools, Enterprise Architecture, Coaching

Industry

Staffing and Recruiting

Description

We are seeking a high-potential Lead Business Analyst to spearhead a strategic workstream within our enterprise data transformation program. This is a high-visibility role for a candidate who functions as a Strategic Partner, bridging the gap between complex data ecosystems and business value. The ideal candidate operates with a Product Owner mindset, driving the domain roadmap rather than just documenting it. They will be the primary liaison for senior stakeholders, ensuring that the client’s data strategy (MDM, Governance, and Integration) translates into tangible business outcomes. Job responsibilities Stakeholder Partnership: Acts as a trusted advisor to senior business leaders, navigating ambiguity and challenging the status quo to define a clear domain vision. Roadmap Stewardship: Functions as a pseudo-Product Owner, taking accountability for value discovery, backlog prioritization, and the strategic "why" behind data initiatives. Client Advisory: Distills complex data concepts into executive-level narratives to influence decision-making and manage expectations across disparate business units. Requirements Engineering: Orchestrates the gathering, documentation, and prioritization of requirements for complex data solutions, including MDM, distribution, and integration. Execution Excellence: Translates high-level business objectives into precise, actionable user stories and functional specifications for engineering teams. Data Lifecycle Management: Applies deep knowledge of Domain Modeling, data quality frameworks, lineage, governance, and data ownership. Structural Knowledge: Leverages experience with MDM programs to understand how data stewardship impacts the broader enterprise. Job qualifications Technical Skills Engineering Partnership: Collaborates closely with Data Engineers and Architects to ensure business logic is accurately reflected in technical designs. Hybrid Fluency: Maintains the professional versatility to lead deep-dive technical sessions with engineers and strategic steering committee meetings with leadership. Enterprise Context: Operates within the context of Business and Enterprise Architecture practices and BI tool consumption (e.g., Tableau, Power BI, QuickSight) to ensure data solutions are scalable. Strategic Stakeholder Management: Proven experience partnering directly with senior/executive leadership to influence and manage expectations. Product/Domain Ownership: A history of driving a product roadmap or a distinct workstream focused on value delivery. Data Domain Expertise (MDM): Deep functional understanding of Master Data Management, including quality, governance, and ownership models. Requirements Lifecycle Mastery: Expert ability to translate high-level business ambiguity into structured functional specifications. BI & Visualization Tooling: Familiarity with how data structure impacts end-user insights in tools like Tableau or Power BI. Enterprise Architecture Frameworks: Exposure to formal frameworks or Business Architecture practices. Technical Data Literacy: Ability to navigate data schemas for high-level data profiling or validation. Professional Skills You enjoy coaching, have led a team and are an advocate for sharing knowledge with others. You have a knack for prioritization, obtaining buy-in from stakeholders and resolving conflicts as they arise. You're resilient and flexible in ambiguous situations and enjoy solving problems from technical and business perspectives. Experience supporting business adoption of new data processes or governance policies. Other things to know Learning & Development There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys. Responsible Use of AI in Recruitment At Thoughtworks, we use AI tools to support our recruitment team with administrative tasks such as drafting communications, scheduling interviews and writing job descriptions. Crucially, our AI tools do not screen, assess, rank or make hiring decisions. Every application is reviewed by our team and all selection decisions are made exclusively by our interviewers and hiring managers. We are committed to fairness and responsible AI. We actively manage our AI systems by testing, monitoring for biased outcomes and implementing mitigation measures. We hold our third-party vendors to these same high standards through a rigorous governance process. For additional information, please see our full Thoughtworks AI Policy for Recruitment. About Thoughtworks Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary. See here our AI policy.

Responsibilities

The Lead Data Business Analyst will act as a trusted advisor to senior business leaders and will take accountability for value discovery and backlog prioritization in data initiatives. They will also translate high-level business objectives into actionable user stories and functional specifications for engineering teams.