Design, develop and maintain Data Catalog, Metadata Management repository/module and Data Lineage through Data Management / Quality tools.
Ensure that Master data management capabilities meets quality requirement.
Report on data issues, data quality improvement initiatives and measurement metrics.
Perform Root Cause Analysis and effectively resolve critical issues within agreed timelines.
Collaborate with stakeholders, Data Governance team, Data Engineers/ IT team, Data Owners, Data Stewards, Data source administrators, platform and software developers to ensure standards, policy, measurement metrics are being met
Ensure that Data Management infrastructure, Policies & Procedures are kept up to date with Data Ecosystem;
Proactively identify gaps as part of Agile Data Quality Improvement initiatives
Collaborate with IT Data Engineering team on Commissioning new pipelines (New source systems, new applications, new products, change requests) and on ETL issues involving Data Quality
Translate business requirements to technical design, data models and manage data quality engineering tasks.
Work with stakeholders, data architects, data owners and stewards to implement data management process, business rules, business decisions, policy, and analyze gap as part of the organization’s data governance requirements.
Document, communicate progress and share improvement plan on Data Quality issues/reported incidents to stakeholders (Heads of Divisions, Data Scientists, ML Engineers, Analysts and Other Data Consumers)
Monitor, across data-lifecycle stages that privacy (data protection), business decision, access, rules, and regulatory requirements are adhered to consistently from sources, storages (hot and cold), metadata updates, job failure logs/data logs, and downstream reporting servers.
Facilitate data audits by auditors
Entry Requirements
Bachelor’s Degree in Computer Science, Engineering, IT, Business or relevant major with good programming and technical skills. Master’s degree in a relevant field will be preferred.
2-5 years of experience within the field of Data Engineering, Data Management, implementing real-time ingestion/streaming, maintaining Big Data Lake/Warehouse and experience in ETL tasks on premise and cloud.
Good understanding of Data lineage, Data Catalog, master data management, metadata management and Data Management tools.
Experience using ETL tools and developing complex pipelines through either Scala/Java/Python or opensource tools.
Expertise in SQL, Apache Spark, Nifi, Airflow, Kafka; Experience in designing and maintaining relational databases and non-SQL data storage. Data Engineering certifications will be an added advantage.
Experience in software development and optimizing code for performance and scalability will be an added advantage