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Technology & Transformation - Engineering - Senior Consultant - ETL Testing

Deloitte -
Bengaluru, Karnataka

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Job details

Qualifications

Jira
CI/CD
Data modeling
Oracle
Business intelligence
Test management tools
Big data
UNIX
Git
Databases
SQL
Pandas
Analysis skills
Bachelor's degree
Machine learning
Continuous integration
Scripting
Rally (agile software)
GitHub
APIs
Agile
B.E.
Linux
Jenkins
Communication skills
Banking
Data warehouse
Python
Shell Scripting

Full job description

Job requisition ID :: 99693

Date: May 26, 2026

Location: Bengaluru

Designation: Senior Consultant

Entity: Deloitte Touche Tohmatsu India LLP

Technology & Transformation - Engineering - Senior Consultant - ETL Testing

Job requisition ID: 99693
Location: Bengaluru
Entity: Deloitte Touche Tohmatsu India LLP

The Team

Deloitte’s Technology & Transformation: EAD: Engineering practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.

Your work profile:

As a Senior Consultant in our Technology & Transformation Team you’ll build and nurture positive working relationships with teams and clients with the intention to exceed client expectations: -

Design, develop and deploy solutions using different tools, design principles and conventions.
Configure robotics processes and objects using core workflow principles in an efficient way; ensure they are easily maintainable and easy to understand.
Understand existing processes and facilitate change requirements as part of a structured change control process.
Solve day to day issues arising while running robotics processes and provide timely resolutions.
Maintain proper documentation for the solutions, test procedures and scenarios during UAT and Production phase.
Coordinate with process owners and business to understand the as-is process and design the automation process flow.

Key skills required:

Design and develop Python-based automation frameworks and reusable utilities for ETL validation and data reconciliation.
Conduct end-to-end ETL testing, including source-to-target validation, transformation logic verification, and data completeness checks.
Write, review, and optimize SQL queries (joins, CTEs, window functions) to validate complex business rules and data transformations.
Execute Unix/Linux commands and shell scripts for ETL job monitoring, file validation, and log analysis.
Work with Mainframe systems for flat file validation, dataset checks, and job executions in ETL processes.
Test data warehouse components such as staging, fact, and dimension tables, including Slowly Changing Dimensions (SCDs).
Integrate automated validation into ETL CI/CD pipelines (Jenkins, GitHub Actions).
Collaborate with ETL developers, data modelers, and business analysts to investigate issues and ensure accurate data flow across banking systems.
Prepare test evidence, automation reports, and dashboards for traceability and coverage metrics.
UG: B. Tech /B.E. in Any Specialization.

Must Have Skills:

Strong proficiency in Python (pandas, pyodbc, data comparison and validation frameworks).
Expertise in SQL — complex joins, aggregations, subqueries, and analytical functions.
Strong understanding of Oracle databases/datawarehouse and relational data modeling.
Proficiency in Unix/Linux commands (grep, awk, sed, shell scripting).
Basic knowledge of Mainframe systems for dataset handling.
Good understanding of Data Warehousing concepts — staging, data marts, fact/dimension modeling, and SCD handling.
Familiarity with test management tools (Rally, JIRA, Qtest) and CI/CD tools (Git, Jenkins).

Good to Have Skills:

Banking domain exposure, especially in: Corporate & Institutional Banking (e.g., treasury, lending, payments, trade finance).
Personal Banking (e.g., retail accounts, loans, deposits, credit cards).
Knowledge of data governance and quality frameworks.
Exposure to API testing for data ingestion and integration layers.
Ability to implement data validation automation within ETL CI/CD pipelines.

Soft Skills:

Strong analytical and problem-solving skills with keen attention to data accuracy.
Excellent communication and collaboration with cross-functional teams.
Ability to work independently in fast-paced Agile environments.
Detail-oriented, proactive, and quality-driven mindset.

Apply Now

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