What are the responsibilities and job description for the Data Quality Engineer position at Intellibus?
Imagine working at Intellibus to engineer platforms that impact billions of lives around the world. With your passion and focus we will accomplish great things together!
Our Platform Engineering Team is working to solve the Multiplicity Problem. We are trusted by some of the most reputable and established FinTech Firms. Recently, our team has spearheaded the Conversion & Go Live of apps which support the backbone of the Financial Trading Industry.
We are seeking a Data Quality Engineer (QE) Test Data Management to ensure the highest standards of software quality and reliability.
We are looking for Engineers who can:
- Develop and implement data quality strategies to maintain accuracy, consistency, and completeness.
- Automate data validation and cleansing processes using SQL and scripting languages.
- Leverage AWS cloud services (S3, Redshift, Glue, Lambda) for data pipeline management and processing.
- Perform data integrity checks, profiling, and anomaly detection using SQL, Python, or Spark.
- Establish data governance frameworks to ensure compliance with industry regulations.
- Partner with ETL teams to enhance pipeline performance and optimize error handling.
- Create dashboards and reports to track and monitor data quality metrics.
- Collaborate with data engineers and business analysts to resolve data quality challenges.
- Develop comprehensive test cases for senior executives and key stakeholders.
- Present and demonstrate working solutions effectively.
- Strong proficiency in MS Excel for data analysis and reporting.
Qualification & Education:
- 7 years of experience in data quality engineering, data validation, or data governance.
- Strong proficiency in SQL (writing complex queries, data validation, stored procedures).
- Experience working with AWS services (Redshift, S3, Glue, Lambda, RDS, Athena).
- Hands-on experience with ETL tools (Talend, Informatica, AWS Glue, DBT).
- Familiarity with data profiling, cleansing, and monitoring frameworks.
- Proficiency in Python, PySpark, or Shell scripting for automation.
- Experience with big data frameworks (Hadoop, Spark) is a plus.
- Knowledge of security testing best practices and regulatory compliance.
- Financial services experience is a plus.
- Testing Tools: JMeter, Gatling, LoadRunner, Postman, RestAssured, SoapUI.
Testing Tools
- Automation Frameworks: Selenium, Cypress, Playwright
- TDM Tools: Delphix, IBM Optim, Informatica TDM
- CI/CD Tools: Jenkins, GitHub Actions, Azure DevOps
- Cloud & Containerization: AWS, Docker, Kubernetes
- Databases: PostgreSQL, MySQL, MongoDB
Work closely with
- Test Data Management
- Test Automation frameworks
- NFR Testing
- Test Methodologies
Our Process
- Schedule a 15-minute Video Call with someone from our Team
- 4 Proctored GQ Tests (< 2 hours)
- Slideware (Presentation)
- 30-45 min Final Video Interview
- Receive Job Offer
If you are interested in reaching out to us, please apply and our team will contact you within the hour.
