You will work with product managers, solution business analysts, data developers & testers, architects and data platform stakeholders to understand the customer business cases, their data needs and confirming the data product quality across multiple dimensions to support improved decision making for the customer.
Key Accountabilities
Understand data product requirements and document data specifications including business rules for data acquisition, processing and presentation
Design data architecture and canonical data models enabling data product/service standardization
Collaborate with supplier teams to build and deliver the data products
Design, build and execute data validation plans for complex data management solutions built on traditional and modern data processing frameworks.
Identify errors, document & communicate them to delivery teams, and collaborate with them to achieve an acceptable data quality standard
Understand the data lineage and prepare data test cases to validate the data during every stage of the data processing journey.
Collaborate with DevOps and Infra team members to build data quality regression suite
Develop database (SQL/No-SQL/Python) scripts for verification of data at extraction, transformation and loading phases by verifying the data mapping & transformation rules.
Manage and mentor junior data analysts to achieve product delivery and data quality objectives
Participate actively in Scrum meetings with the development team, Product Owner, Architects and Scrum Master and provide up-to-date testing feedback.
Collaborate with Product Manager to improve product testing through regression testing and User Acceptance Test (UAT) processes.
Responsible for overall data product and quality strategy for Data Management from requirement through test coverage planning to product delivery with relentless focus on quality and continuous improvement for compliance.
Key Experience and Qualifications
Degree level education in Mathematics, Computing or Engineering discipline or equivalent experience.
10+ years of experience at various levels of Data management and/or data quality roles with at least 3+ years leading a data team
Experience in documenting, planning, designing and executing data engineering and data quality verification processes in the context of complex Data Engineering & Analytics projects.
Strong experience with SQL, Python, PySpark for data analysis, validation against product specification and data reconciliation, preferably in Azure Data Platform setup
Experience of working in an agile environment, within a self-organizing team, managing small teams of data analysts and/or data testers
Desirable
Experienced in DevOps methodology, preferably using Azure DevOps.
Experience with modern data integration/engineering tools is a plus.
Exposure to test methodologies and developing test plans using Microsoft based test tools like MTM, Azure Test Plans
Exposure to planning non-functional testing in a large Data Processing environment including performance, load and integration testing
Work Experience
Data Architect
A Data Architect works in complex data projects with a focus on
Collating data requirements from data consumer teams, standardizing the data architecture and working with data supply teams to implement data products
Building data product validation plans and executing them to ensure the delivery of quality data products
You will work with product managers, solution business analysts, data developers & testers, architects and data platform stakeholders to understand the customer business cases, their data needs and confirming the data product quality across multiple dimensions to support improved decision making for the customer.
Key Accountabilities
Understand data product requirements and document data specifications including business rules for data acquisition, processing and presentation
Design data architecture and canonical data models enabling data product/service standardization
Collaborate with supplier teams to build and deliver the data products
Design, build and execute data validation plans for complex data management solutions built on traditional and modern data processing frameworks.
Identify errors, document & communicate them to delivery teams, and collaborate with them to achieve an acceptable data quality standard
Understand the data lineage and prepare data test cases to validate the data during every stage of the data processing journey.
Collaborate with DevOps and Infra team members to build data quality regression suite
Develop database (SQL/No-SQL/Python) scripts for verification of data at extraction, transformation and loading phases by verifying the data mapping & transformation rules.
Manage and mentor junior data analysts to achieve product delivery and data quality objectives
Participate actively in Scrum meetings with the development team, Product Owner, Architects and Scrum Master and provide up-to-date testing feedback.
Collaborate with Product Manager to improve product testing through regression testing and User Acceptance Test (UAT) processes.
Responsible for overall data product and quality strategy for Data Management from requirement through test coverage planning to product delivery with relentless focus on quality and continuous improvement for compliance.
Key Experience and Qualifications
Degree level education in Mathematics, Computing or Engineering discipline or equivalent experience.
10+ years of experience at various levels of Data management and/or data quality roles with at least 3+ years leading a data team
Experience in documenting, planning, designing and executing data engineering and data quality verification processes in the context of complex Data Engineering & Analytics projects.
Strong experience with SQL, Python, PySpark for data analysis, validation against product specification and data reconciliation, preferably in Azure Data Platform setup
Experience of working in an agile environment, within a self-organizing team, managing small teams of data analysts and/or data testers
Desirable
Experienced in DevOps methodology, preferably using Azure DevOps.
Experience with modern data integration/engineering tools is a plus.
Exposure to test methodologies and developing test plans using Microsoft based test tools like MTM, Azure Test Plans
Exposure to planning non-functional testing in a large Data Processing environment including performance, load and integration testing
