Management Trainee

City: Bengaluru

State/Province: Karnataka

Posting Start Date: 1/27/26

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients' most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.

Job Description:

Mangement Trainee

Role Purpose

The purpose of the role is to provide effective technical support to the process and actively resolve client issues directly or through timely escalation to meet process SLAs.

• Overview:
  This role will support Private Equity enterprise data with a focus on reconciling, validating,
  and standardizing historical and ongoing datasets. The role centers on cash activity data,
  portfolio company financial data, and other key operational datasets that require high
  accuracy, completeness, and governance oversight. This position is an analyst-level role,
  and requires strong analytical skills, attention to detail, and the ability to work within
  structured data workflows.
  Key Responsibilities - - - - - - - - -
  Reconcile historical and current data, including cash activity and portfolio company
  f
  inancial data, across multiple internal and external sources.
  Perform backfilling of historical data to ensure completeness and alignment with
  current standards.
  Validate data accuracy, investigate discrepancies, and coordinate resolution with
  relevant teams.
  Ensure timely data uploads, reconciliation cycles, and documentation of
  exceptions.
  Apply data governance standards, including naming conventions, quality controls,
  lineage tracking, and audit requirements.
  Monitor data quality metrics and maintain standardized reporting across datasets.
  Provide regular status updates on reconciliation progress, issues, blockers, and
  expected timelines.
  Collaborate with key stakeholders to support data-related initiatives.
  Contribute to process improvements for data quality, reconciliation efficiency, and
  automation opportunities.
  Qualifications - - - - - - -
  Bachelor's degree in Finance, Accounting, Data Science, Engineering, or a related
  discipline.
  1-3 years of experience in data reconciliation, data governance, data operations, or
  f
  inancial data analysis.
  Strong analytical and problem-solving skills with a high attention to detail.
  Experience working with large datasets and structured data environments.
  Proficiency in Excel and familiarity with SQL or other query tools (preferred).
  Understanding of financial statements, cash movements, and portfolio company
  reporting (preferred).
  Familiarity with private equity is a plus.
  Familiarity with 73Strings is a plus. - - -
  Strong communication skills and the ability to provide clear and concise status
  updates.
  Ability to work independently, manage priorities, and meet tight deadlines in a
  fast-paced environment.
  Competencies - - - - -
  Data accuracy and quality orientation
  Process discipline and documentation
  Logical and structured thinking
  Proactive issue identification and remediation
  Collaboration across teams and time zones

• Overview:
  This role will support Private Equity enterprise data with a focus on reconciling, validating,
  and standardizing historical and ongoing datasets. The role centers on cash activity data,
  portfolio company financial data, and other key operational datasets that require high
  accuracy, completeness, and governance oversight. This position is an analyst-level role,
  and requires strong analytical skills, attention to detail, and the ability to work within
  structured data workflows.
  Key Responsibilities - - - - - - - - -
  Reconcile historical and current data, including cash activity and portfolio company
  f
  inancial data, across multiple internal and external sources.
  Perform backfilling of historical data to ensure completeness and alignment with
  current standards.
  Validate data accuracy, investigate discrepancies, and coordinate resolution with
  relevant teams.
  Ensure timely data uploads, reconciliation cycles, and documentation of
  exceptions.
  Apply data governance standards, including naming conventions, quality controls,
  lineage tracking, and audit requirements.
  Monitor data quality metrics and maintain standardized reporting across datasets.
  Provide regular status updates on reconciliation progress, issues, blockers, and
  expected timelines.
  Collaborate with key stakeholders to support data-related initiatives.
  Contribute to process improvements for data quality, reconciliation efficiency, and
  automation opportunities.
  Qualifications - - - - - - -
  Bachelor's degree in Finance, Accounting, Data Science, Engineering, or a related
  discipline.
  1-3 years of experience in data reconciliation, data governance, data operations, or
  f
  inancial data analysis.
  Strong analytical and problem-solving skills with a high attention to detail.
  Experience working with large datasets and structured data environments.
  Proficiency in Excel and familiarity with SQL or other query tools (preferred).
  Understanding of financial statements, cash movements, and portfolio company
  reporting (preferred).
  Familiarity with private equity is a plus.
  Familiarity with 73Strings is a plus. - - -
  Strong communication skills and the ability to provide clear and concise status
  updates.
  Ability to work independently, manage priorities, and meet tight deadlines in a
  fast-paced environment.
  Competencies - - - - -
  Data accuracy and quality orientation
  Process discipline and documentation
  Logical and structured thinking
  Proactive issue identification and remediation
  Collaboration across teams and time zones