Bain \& Company is a global management consulting that helps the world’s most ambitious change makers define the future. Across 65 offices in 40 countries, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition and redefine industries. Since our founding in 1973, we have measured our success by the success of our clients, and we proudly maintain the highest level of client advocacy in the industry.
In 2004, the firm established its presence in the Indian market by opening the Bain Capability Center (BCC) in New Delhi. The BCC is now known as BCN (Bain Capability Network) with its nodes across various geographies. BCN is an integral and largest unit of (ECD) Expert Client Delivery. ECD plays a critical role as it adds value to Bain's case teams globally by supporting them with analytics and research solutioning across all industries, specific domains for corporate cases, client development, private equity diligence or Bain intellectual property. The BCN comprises of Consulting Services, Knowledge Services and Shared Services.
- *Who you will work with**
We are looking for a detail\-oriented and analytically driven Associate – Data Operations to join Bain’s Data Business COE, working directly with the Helix Data Operations team. Helix is Bain’s comprehensive platform for company data and market intelligence — enabling consulting teams and investors to access millions of company profiles, generate lists for diligences, deal sourcing, sector profiles, and customer targeting.
This role sits within the Data Business COE and is central to maintaining the data integrity that powers Helix. Your primary mission will be to drive data quality in our proprietary knowledge graph — ensuring coverage, cleanliness, and business\-sense integrity — using SQL and scalable automation techniques across a dataset spanning 50–70M companies.
- Drive the data management and quality control process end\-to\-end; enhance and maintain the proprietary database
- Validate and apply data quality checks while collecting data from different sources; ensure strict compliance with legal guidelines
- Gather requirements and business process knowledge to clean and transform data geared toward end\-user needs
- Mine data across 50–70M companies, reviewing 500–600 data points per company to surface coverage, cleanliness, and business\-sense issues
- Work with databases and run queries using SQL (with strong emphasis on Snowflake SQL) for data retrieval and analysis
- Assist in assessing new data sources brought into the knowledge graph; respond to onshore team and client questions around data and insights
- Devise smart, scalable ways to use data, including tagging techniques and secondary research using key data sources
- Build and execute daily workplans; provide tool\-based technical expertise to team members as required
- Support multiple projects across workstreams to deliver high\-quality, zero\-defect deliverables; leverage manager’s guidance on complex pieces
- Coordinate with internal stakeholders across workstreams; proactively flag and address roadblocks to avoid yield loss
- 3–4 years of experience in areas related to Business Analysis, Data Management, or Business Intelligence; hands\-on experience in data handling and SQL
- Hands\-on experience in research and analytics with exposure to key secondary data sources; strong problem\-solving and consulting skillset
- 1\+ years of experience at a data provider, data business, or business intelligence firm; ideally at a firm catering to financial or strategy sectors (preferred)
- Exposure to private equity, management consulting, or data\-driven business environments is a plus
- *Technical Skills — Preferred**
- Strong proficiency in Excel, PowerPoint, SQL, and data visualization tools (e.g., Tableau); familiarity with cloud platforms (AWS/Azure) and GenAI tools/technology is a strong preference
- Hands\-on experience with Snowflake SQL, including complex queries, virtual warehouses, and Snowflake\-specific functions for data analysis and transformation
- Experience building data health dashboards using Tableau or similar visualization tools to monitor data quality metrics
- Experience building data cleanup solutions that combine automation and human reviewer inputs
- *Soft Skills \& Mindset**
- Strong attention to detail with a zero\-defect mentality — you take ownership of data quality and take pride in accuracy
- Comfortable working with large\-scale datasets and translating complexity into clean, structured, pragmatic outputs
- Collaborative team player who communicates clearly across technical and non\-technical audiences
- Proven self\-starter comfortable in remote or distributed team settings, with strong problem\-solving and organisational skills
- Curious learner who stays current with data tooling, analytics best practices, and emerging GenAI/AI capabilities
- *Education**
- Required: Graduate / post\-graduate from a top\-tier institute, or equivalent analytical/statistical course from a Tier 1 university
- Preferred: Concentration in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, Econometrics, Business Analytics, or Market Research
- *What makes us a great place to work**
We are proud to be consistently recognized as one of the world's best places to work, a champion of diversity and a model of social responsibility. We are currently ranked the \#1 consulting firm on Glassdoor’s Best Places to Work list, and we have maintained a spot in the top four on Glassdoor's list for the last 12 years. We believe that diversity, inclusion and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. We are publicly recognized by external parties such as Fortune, Vault, Mogul, Working Mother, Glassdoor and the Human Rights Campaign for being a great place to work for diversity and inclusion, women, LGBTQ and parents..