Job description:
DATA ENGINEERING TEAM OVERVIEW
At AB InBev Data Engineering, we have a dream: build an analytics-driven company. Our mission is to provide data to power all analytics initiatives. We are creating agile teams of data engineers, architects, analysts and scrum masters to deliver on our mission.
· As the QA Engineer, you will own the validation of data engineering project outputs, acting as the point of control for the release of developments to production, and a key point of contact for the validation of technical and functional requirements.
· You will be passionate about quality, guiding teams in embracing project delivery best practices. The QA Engineer will work closely with the data engineering team to ensure the successful, on-time, delivery of high-quality data.
· Manage and maintain large data sets to ensure high quality of data for analyses
· Engage with business partners at all levels of organization and influence future based on insights
PURPOSE OF ROLE
- Ensure that data provision meets the business and platform performance requirements, and that Data Engineering standards are applied to all deliveries in each sprint.
- Review Test Plan and Test scenarios with QA Lead.
- Maintain efficient, reusable, and reliable data validation and solution QA processes
- Drive continuous improvement in QA techniques and tools
- Own and execute the delivery of project milestones and modules leveraging feedback
- Engage with stakeholders and assist the entire process of project delivery
- Tracking on key milestones of a project, while running agile routines for the team
REQUIRED QUALIFICATIONS, EXPERIENCE, SKILLS
- 3 - 6 years of relevant experience, in QA
- Advanced working SQL knowledge, designing complex SQL Logics and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience with at least one end to end data platform complete project validations using ETL & data warehousing concepts along with some exposure to Automation on ETL part.
- Validate visualization using BI reporting tools.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with structured and unstructured datasets from multiple data source.
- Validate processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large, disconnected datasets.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Experience with big data tools: Hadoop, Azure DevOps, Hive
- Experience in Azure Data Factory (ADF) & Azure Data Bricks (ADB)
- Experience with relational SQL and NoSQL databases
- Experience with data pipeline and workflow management tools
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Data management: SQL, Advanced Excel, BI reporting Tools.
- Good to have skills - basics of BIG DATA architecture, Spark, Kafka, SAP (basics),Unix..
Skills –
- Advanced working SQL knowledge, designing complex SQL Logics and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience with at least one end to end data platform complete project validations using ETL & data warehousing concepts along with some exposure to Automation on ETL part.
- Validate visualization using BI reporting tools.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with structured and unstructured datasets from multiple data source.
- Validate processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large, disconnected datasets.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Experience with big data tools: Hadoop, Azure DevOps, Hive
- Experience in Azure Data Factory (ADF) & Azure Data Bricks (ADB)
- Experience with relational SQL and NoSQL databases
- Experience with data pipeline and workflow management tools
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Data management: SQL, Advanced Excel, BI reporting Tools.
- Good to have skills - basics of BIG DATA architecture, Spark, Kafka, SAP (basics), Unix
Qualification, Course, Specialization - 3 - 6 years of relevant experience, in QA
