Data Test Engineer

Job Title: Data Test Engineer

Job Summary:

We are seeking a skilled Data Test Engineer with strong technical capabilities and a deep understanding of ETL development. The ideal candidate will have experience in coding languages such as Python, SQL, and XML, along with expertise in data warehousing concepts and architecture techniques. This role requires extensive troubleshooting skills to solve complex technical issues in ETL processes. Proficiency in data warehousing methods like Operational Data Store (ODS), Data Marts (DM), Enterprise Data Warehouse (EDW), and Relational OLAP (ROLAP) is essential.

Top 3 Required Skills:

1. S3
2. Hadoop
3. PostgreSQL

Key Responsibilities:

• Quality Assurance Experience: Utilize 5+ years of software quality assurance experience on enterprise-level applications, specifically in data warehouse testing.
• SQL Expertise: Write complex SQL queries to support various testing needs such as data validation and regression, assess testability of requirements, and develop comprehensive test plans for business and technological solutions.
• Testing Phases: Test across multiple project phases, especially in medium to large-scale projects, ensuring data integrity through validation.
• Data Governance Knowledge: Apply principles of information governance in a testing context.
• Data Warehousing and Data Mart Testing: Execute testing for data warehouses and data marts with clear understanding.
• Test Data Preparation: Identify test data preparation techniques and transform complex business logic into SQL or PL/SQL queries.
• Testing Lifecycle Proficiency: Maintain thorough knowledge of Software Test Life Cycle, Test Case Life Cycle, Defect Life Cycle, and requirements traceability.
• Test Case Management: Prepare, execute, and track test cases; ensure requirements are accurately traced with RTM.
• Automation and Tools: Leverage QA automation tools with Python for test automation.
• ETL Testing: Conduct ETL testing with extensive SQL proficiency, handling large data sets within a Data Quality Framework.
• Data Analysis and Profiling: Perform data analysis, including profiling, auditing, balancing, and reconciliation.
• Defect Tracking and Resolution: Use tools such as Jira and ALM for tracking and managing defects.
• SQL Tuning: Enhance SQL performance through optimization of queries, stored procedures, and views.
• Attention to Detail: Bring an analytical mindset, focusing on detail-oriented testing and analysis.
• Data Modeling Knowledge: Understand data models and entity-relationship diagrams for effective testing.

Technical Requirements:

• Cloud and Data Lake Expertise: Experience with Snowflake, AWS S3, Hadoop Data Lake, PostgreSQL, MongoDB, and other cloud technologies.
• ETL Tools Proficiency: Skilled in Informatica PowerCenter and Informatica BDM for ETL processes.
• Data Integration and Analytics: Experience in data extraction, transformation, and loading from various data repositories (structured and semi-structured).
• Data Modeling and Design: Knowledge in designing data marts and data warehouses following data modeling principles.
• Problem Solving: Strong analytical skills to address complex issues efficiently.
• Independent and Collaborative Work Style: Self-motivated with the ability to work independently and as part of a team, with a commitment to delivering high-quality service.
• Mentorship and Learning: Quick learner who is willing to guide team members and foster a knowledge-sharing environment.

Preferred Qualifications:

• Experience with Large Data Sets: Familiarity with data quality frameworks, data cleansing, and data analysis methods.
• Adaptability and Multitasking Skills: Ability to handle multiple tasks in a dynamic environment, responding to changes with urgency and flexibility.

Attributes:

• Ownership: A proactive self-starter who takes initiative, ownership, and responsibility for tasks.
• Team Player: Works collaboratively within a team environment and strives to achieve high-quality results.