Senior data management specialist

Senior Data Management Specialist

Location: Hyderabad

Experience: 7+ Years

Role Type: Data Management / Data Analysis / Business Intelligence

Industry: Banking / Financial Services

Role Overview

We are looking for an experienced Senior Data Management Specialist with 7+ years of experience in data discovery, data analysis, data profiling, and data management, preferably within the banking or financial services industry.

The ideal candidate will have a strong understanding of consumer banking products and business processes, excellent SQL and data analysis skills, and hands-on experience working with business intelligence tools and enterprise database platforms. The candidate should be comfortable exploring large and complex datasets, identifying data patterns and issues, and translating business requirements into meaningful data insights.

This role requires strong analytical thinking, attention to detail, collaboration skills, and the ability to work independently in a fast-paced enterprise environment.

Key Responsibilities

Data Discovery & Analysis

Perform detailed data discovery, exploration, profiling, and analysis across multiple enterprise data sources. Analyze large and complex datasets to identify trends, patterns, relationships, anomalies, and data quality issues. Understand business requirements and translate them into data analysis and discovery activities. Investigate data across multiple systems and sources to understand how information is captured, transformed, stored, and consumed. Identify gaps, inconsistencies, and opportunities for improving data quality and usability. Conduct root-cause analysis for data-related issues and provide actionable recommendations. Support business and technology teams with data-driven insights and analysis.

SQL & Data Profiling

Develop and execute complex SQL queries for data extraction, validation, profiling, reconciliation, and analysis. Perform data profiling to understand data structures, completeness, accuracy, consistency, and relationships. Work with large datasets and optimize queries where required for efficient analysis. Perform data reconciliation across multiple database systems and applications. Validate data against business rules and expected outcomes. Document findings, data relationships, assumptions, and analysis results.

Business Intelligence & Data Analysis Tools

Use commonly adopted Business Intelligence and data analysis tools such as Tableau, SAS, Oracle, Microsoft tools, or similar platforms. Perform data exploration and analysis using both SQL and non-SQL tools and techniques. Create or support analytical views, reports, dashboards, and data extracts where required. Interpret data from multiple sources and communicate findings to technical and business stakeholders. Support data-driven decision-making by providing accurate and well-structured analysis.

Database & Technology Environment

Work with multiple database management systems, including: Amazon Redshift Oracle Microsoft SQL Server Other relational and enterprise database platforms Work across different operating systems, including Windows and Unix/Linux environments. Understand database structures, schemas, tables, relationships, keys, and data dependencies. Investigate data across heterogeneous technology environments. Collaborate with engineering and technology teams to understand upstream and downstream data flows.

Consumer Banking & Financial Services

Apply strong knowledge of consumer banking and financial products while performing data analysis and discovery. Understand banking business processes and how they impact data creation, processing, and consumption. Analyze data in the context of banking products, customer journeys, accounts, transactions, and related business processes. Work closely with business stakeholders to understand financial services requirements and translate them into data analysis activities. Ensure analysis and recommendations align with business objectives and applicable financial services practices.

Data Management & Data Design

Support enterprise data management initiatives and data-related projects. Contribute to data design activities, including understanding data models, structures, relationships, and dependencies. Assist with defining and documenting data requirements and business rules. Support data governance, data quality, and data management activities as required. Identify opportunities to improve data consistency, accessibility, and reliability. Partner with data architects, engineers, analysts, and business teams on data management initiatives.

Agile Delivery

Participate in Agile development and delivery processes. Collaborate with Product Owners, Business Analysts, Data Engineers, Developers, QA teams, and other stakeholders. Participate in Agile ceremonies such as sprint planning, daily stand-ups, backlog discussions, reviews, and retrospectives. Provide data analysis and technical inputs throughout the project lifecycle. Take ownership of assigned deliverables and ensure timely completion.

Stakeholder Collaboration

Work effectively with both technical and business stakeholders. Communicate complex data findings in a clear and understandable manner. Collaborate across teams to resolve data issues and deliver business outcomes. Take initiative in identifying potential issues and recommending solutions. Manage multiple priorities while maintaining a high level of accuracy. Build strong working relationships with cross-functional teams.

Required Skills & Experience

7+ years of professional experience in data management, data analysis, data discovery, data profiling, business intelligence, or a closely related field. Strong understanding of consumer banking products and business processes. Strong hands-on experience with SQL and data analysis/profiling. Experience performing data discovery and analysis using one or more commonly used BI/data analysis tools such as: Tableau SAS Oracle Microsoft data/BI tools Similar enterprise data analysis platforms Strong understanding of data structures, relationships, data quality, and profiling concepts. Experience working with multiple database management systems, such as: Amazon Redshift Oracle Microsoft SQL Server Other enterprise relational databases Experience working in Windows and Unix/Linux environments. Ability to analyze data from multiple sources and identify discrepancies or patterns. Strong analytical and problem-solving skills. Ability to work independently and take initiative. Strong collaboration and communication skills. Excellent attention to detail. Ability to manage complex data analysis assignments and deliver accurate results.

Desirable Skills & Experience

Experience with data exploration using both SQL and non-SQL tools and techniques. Experience with data profiling and data quality analysis. Experience in data design or enterprise data management. Experience working with data models, schemas, and data lineage. Knowledge of data governance and data quality practices. Experience working in an Agile/Scrum environment. Previous experience in the financial services or banking industry. Experience working with consumer banking or related financial products. Experience collaborating with large enterprise technology and business teams. Exposure to cloud-based data platforms and modern data technologies is an advantage.

Key Competencies

Data Discovery & Exploration Data Analysis & Profiling Advanced SQL Data Quality & Validation Business Intelligence Database Analysis Consumer Banking Domain Knowledge Data Management Data Design Analytical Problem Solving Stakeholder Management Agile Delivery Attention to Detail Communication & Collaboration Ownership and Initiative

Preferred Candidate Profile

The ideal candidate will be a senior data professional with strong SQL and analytical capabilities, combined with practical experience in enterprise data environments and a solid understanding of consumer banking. The candidate should be able to independently explore complex datasets, work across multiple databases and tools, identify data issues, and communicate meaningful findings to both technical and business stakeholders.