Senior Data QA Engineer

2 Months ago • 4 Years + • Quality Assurance

Job Summary

Job Description

N-iX seeks a Senior Data QA Engineer to contribute to the digital transformation of a major school transportation provider. Responsibilities include creating and improving test plans for data functionalities, establishing data quality standards, supporting team members, and improving testing processes. Collaboration with data engineers, scientists, and stakeholders is crucial for integrating and validating data within data warehousing solutions like Snowflake, Redshift, or BigQuery. The role involves data validation, ETL process testing, root cause analysis, and staying updated on industry trends. Experience with data analysis, QA, or automation (4+ years) is required, along with proficiency in SQL and data warehousing.
Must have:
  • 4+ years exp. in data analysis/QA/automation
  • Test plan creation & execution
  • Data quality frameworks knowledge
  • Snowflake/Redshift/BigQuery exp.
  • SQL proficiency
  • Detailed documentation skills
  • Strong analytical & problem-solving skills
Good to have:
  • Data analysis tools (SQL, Python, R)
  • Database & Kafka knowledge
  • Git & CI/CD familiarity
  • Automation tool experience
Perks:
  • Flexible working format
  • Competitive salary
  • Personalized career growth
  • Professional development tools
  • Education reimbursement
  • Corporate events

Job Details

N-iX is seeking for a Senior Data QA Engineer

Our customer is the leading school transportation provider in North America, being the owner of more than a half of all yellow school buses in the United States. Every day, the company completes 5 million student journeys, moving more passengers than all U.S. airlines combined and delivers reliable, quality services for 1,100 school districts. 

N-iX has built a successful cooperation with the client delivering a range of complex initiatives. As a result, N-iX has been selected as a strategic long-term partner to drive the digital transformation on an enterprise level, fully remodeling the technology landscape for 55,000 employees and millions of people across North America. 

 

Responsibilities:

  • Create and Improve Test Plans: Develop and improve test plans for data-related functionalities.
  • Test Automation Setup: Prepare the basis for test automation setup.
  • Establish Data Quality Standards: Enforce and improve data quality standards across datasets.
  • Support Team Members: Provide recommendations and support to QA team members.
  • Improve Testing Processes: Contribute to process improvements within the testing team.
  • Collaboration with Teams: Work closely with data engineers, data scientists, business analysts, and stakeholders to integrate and validate data within data warehousing solutions like Snowflake, Redshift, or BigQuery.
  • Communicate Findings: Report issues and resolutions to both technical and non-technical stakeholders.
  • Design and Document Test Cases: Design and document test cases for data validation, ETL processes, and data workflows.
  • Data Validation & Integrity Checks: Ensure accuracy, consistency, and completeness of data.
  • Analyze Data Profiles: Analyze data structures, patterns, and anomalies for effective quality assessment.
  • Various Types of Testing: Perform functional, regression, integration, and performance testing on data pipelines and transformations.
  • Root Cause Analysis: Investigate and resolve data-related issues through root cause analysis.
  • Stay Updated: Keep up with trends, tools, and best practices in data QA.

Requirements:

  • 4+ years of experience in data analysis, quality assurance, or data automation.
  • Test Plan Development: Experience creating and executing test plans, cases, and scripts for data quality assurance.
  • Data Quality Frameworks: Knowledge of frameworks, profiling, validation, and cleansing techniques.
  • Data Warehousing & ETL/ELT: Experience with Snowflake, Redshift, BigQuery, and data modeling.
  • Proficiency in SQL: Experience with relational databases like SQL, MySQL, PostgreSQL.
  • Documentation: Ability to create detailed documentation of data quality processes and standards.
  • Analytical Skills: Strong analytical and problem-solving skills with attention to detail.
  • Intermediate English Proficiency.
  • Ukrainian language - Advanced.

Nice to Have:

  • Proficiency in Data Analysis Tools: Knowledge of SQL, Python, R, or similar languages for data querying and manipulation.
  • Database & Kafka Knowledge: Familiarity with databases and Kafka.
  • Version Control & CI/CD: Familiarity with Git and CI/CD pipelines.
  • Automation Experience: Experience with automation tools and methodologies.

We offer*:

  • Flexible working format - remote, office-based or flexible
  • A competitive salary and good compensation package
  • Personalized career growth
  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
  • Active tech communities with regular knowledge sharing
  • Education reimbursement
  • Memorable anniversary presents
  • Corporate events and team buildings
  • Other location-specific benefits

*not applicable for freelancers

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