EY - GDS Consulting - AI and DATA - Insurance Domain ETL Testing - Manager

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Job Description for Lead Data Engineer QA

Rank – Manager

Location – Bengaluru/Chennai/Kerela/Kolkata

Objectives and Purpose

• The Lead Data Engineer QA will be responsible for testing business intelligence and data warehouse solutions, both in on-premises and cloud platforms. We are seeking an innovative and talented individual who can create test plans, protocols, and procedures for new software. In addition, you will be supporting build of large-scale data architectures that provide information to downstream systems and business users.

Your key responsibilities

• Design and execute manual and automatic test cases, including validating alignment with ELT data integrity and compliance.
• Support conducting QA test case designs, including identifying opportunities for test automation and developing scripts for automatic processes as needed.
• Follow quality standards, conduct continuous monitoring and improvement, and manage test cases, test data, and defect processes using a risk-based approach as needed.
• Ensure all software releases meet regulatory standards, including requirements for validation, documentation, and traceability, with particular emphasis on data privacy and adherence to infrastructure security best practices.
• Proactively foster strong partnerships across teams and stakeholders to ensure alignment with quality requirements and address any challenges.
• Implement observability within testing processes to proactively identify, track, and resolve quality issues, contributing to sustained high-quality performance.
• Establish methodology to test effectiveness of BI and DWH projects, ELT reports, integration, manual and automation functionality
• Work closely with product team to monitor data quality, integrity, and security throughout the product lifecycle, implementing data quality checks to ensure accuracy, completeness, and consistency.
• Lead the evaluation, implementation and deployment of emerging tools and processes to improve productivity.
• Develop and maintain scalable data pipelines, in line with ETL principles, and build out new integrations, using AWS native technologies, to support continuing increases in data source, volume, and complexity.
• Define data requirements, gather, and mine data, while validating the efficiency of data tools in the Big Data Environment.
• Establish methodology to test effectiveness of BI and DWH projects, ELT reports, integration, manual and automation functionality.
• Implement processes and systems to provide accurate and available data to key stakeholders, downstream systems, and business processes.
• Partner with Business Analytics and Solution Architects to develop technical architectures for strategic enterprise projects and initiatives.
• Coordinate with Data Scientists to understand data requirements, and design solutions that enable advanced analytics, machine learning, and predictive modelling.
• Mentor and coach junior Data Engineers on data standards and practices, promoting the values of learning and growth.
• Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.

To qualify for the role, you must have the following:

Essential skillsets

• Bachelor’s degree in Engineering, Computer Science, Data Warehousing, or related field
• 10+ years of experience in software development, data science, data engineering, ETL, and analytics reporting development
• Understanding of project and test lifecycle, including exposure to CMMi and process improvement frameworks
• Experience designing, building, implementing, and maintaining data and system integrations using dimensional data modelling and development and optimization of ETL pipelines
• Proven track record of designing and implementing complex data solutions
• Understanding of business intelligence concepts, ETL processing, dashboards, and analytics
• Testing experience in Data Quality, ETL, OLAP, or Reports
• Knowledge in Data Transformation Projects, including database design concepts & white box testing
• Experience in cloud based data solution – AWS/Azure
• Demonstrated understanding and experience using:
  • Cloud-based data solutions (AWS, IICS, Databricks)
  • GXP and regulatory and risk compliance
  • Cloud AWS infrastructure testing
  • Python data processing
  • SQL scripting
  • Test processes (e.g., ELT testing, SDLC)
  • Power BI/Tableau
  • Script (e.g., perl and shell)
  • Data Engineering Programming Languages (i.e., Python)
  • Distributed Data Technologies (e.g., Pyspark)
  • Test Management and Defect Management tools (e.g., HP ALM)
  • Cloud platform deployment and tools (e.g., Kubernetes)
  • DevOps and continuous integration
  • Databricks/ETL
• Understanding of database architecture and administration
• Utilizes the principles of continuous integration and delivery to automate the deployment of code changes to elevate environments, fostering enhanced code quality, test coverage, and automation of resilient test cases
• Processes high proficiency in code programming languages (e.g., SQL, Python, Pyspark, AWS services) to design, maintain, and optimize data architecture/pipelines that fit business goals
• Strong organizational skills with the ability to manage multiple projects simultaneously and operate as a leading member across globally distributed teams to deliver high-quality services and solutions
• Excellent written and verbal communication skills, including storytelling and interacting effectively with multifunctional teams and other strategic partners
• Strong problem solving and troubleshooting skills
• Ability to work in a fast-paced environment and adapt to changing business priorities

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