Data Integration: Designing, implementing, and maintaining data integration processes. Ensuring smooth data flow between different systems and databases. Managing ETL (Extract, Transform, Load) and ELT (Extract, Load and Transform) processes.
Data Quality Management: Implementing and maintaining data quality standards. Identifying and resolving data quality issues. Collaborating with data stewards to improve data quality.
Data Warehousing: Maintaining data warehouses. Optimizing data storage and retrieval processes. Managing and monitoring data warehouse performance.
Data Governance: Establishing and enforcing data governance policies. Collaborating with stakeholders to define data ownership and access policies. Ensuring compliance with data privacy regulations.
Data Security: Implementing and monitoring data security measures. Managing access controls and permissions. Conducting regular security audits and assessments.
Data Monitoring and Troubleshooting: Monitoring data pipelines for errors and anomalies. Investigating and resolving data-related issues. Implementing proactive measures to prevent data problems.
Performance Optimization: Tuning and optimizing database and data processing performance. Identifying and resolving bottlenecks in data pipelines. Implementing best practices for data performance.
Collaboration: Collaborating with cross-functional teams business stakeholders. Participating in data-related projects and initiatives. Providing support to end-users.
Documentation: Documenting data processes, workflows, and configurations. Creating and maintaining documentation for data-related policies and procedures.
Expertise in Data store architectures like Modern data warehouse (MDW) and Lakehouse architecture.
Must be familiar with extract, load, transform (ELT) and extract, transform, load (ETL) tools.
Should have solid knowledge of data processing languages, including SQL and Python
Should be proficient in using the following, to create data processing solutions: SSIS, Azure Data Factory (ADF), Azure Synapse Analytics, Azure Event Hubs, Azure Data Lake Storage, Azure Databricks.
Strong analytical and critical-thinking skills.
Domain knowledge related to the industry they are working in.
Effective communication skills to convey complex data insights to non-technical stakeholders.
