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 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 implement automated test frameworks for ETL / ELT pipelines.
• Validate source-to-target data reconciliation, transformation logic, and business rules.
• Develop automated test scripts for data completeness, accuracy, timeliness, and integrity checks.
• Perform database, file, and API level testing across structured and semi-structured data.
• Create reusable automation components for row counts, checksum validation, null checks, and referential integrity.
• Execute regression, integration, and system testing for data pipelines.
• Analyze test failures, identify root causes, and work closely with data engineers to resolve issues.
• Validate incremental loads, CDC logic, and historical data migrations.
• Integrate automation tests with CI/CD pipelines.
• Prepare test plans, test cases, defect reports, and execution summaries.

Technical Skills

• ETL / Data Testing: Strong understanding of ETL concepts, data warehousing, Data lakes and UNIX.
• Automation: Python / PyTest / Robot Framework / TestNG
• SQL: Advanced SQL for complex data validation
• Data Platforms: Databricks, Snowflake, Redshift, Big Query, Synapse
• ETL Tools: Informatica, Ab Initio, Talend, DataStage, DBT (any)
• Cloud: AWS / Azure / GCP (hands-on experience with at least one)
• CI/CD: Jenkins, Azure DevOps, GitHub Actions
• Data Formats: Parquet, Avro, JSON, CSV, XML
• Bonus: Great Expectations, Deequ, Soda, Monte Carlo

Qualifications:

• B. E. / B. Tech / MCA / M.E / M. Tech / MSc in Computer Science.