Data Masking Senior Engineer Role

--- Job Title: Senior Data Engineer – Data Masking | SQL Server | Snowflake | Databricks Location: Remote (India) Client: AIGREV (US Client) Employment Type: 6-Month Contract Job Summary We are seeking a highly skilled Senior Data Engineer to support a US-based client (AIGREV) on a 6-month remote contract. The primary focus of this role is implementing enterprise data masking solutions as part of Data Migration and ETL execution across Enterprise Data Hub (EDH) environments. Candidates must have prior hands-on experience designing and implementing data masking during large-scale data migration and ETL/ELT projects. Experience in SQL Server Dynamic Data Masking (DDM), Azure Data Factory (ADF), Snowflake, and Databricks is essential. The role requires collaboration with US stakeholders and flexibility to work during overlapping US business hours. --- Primary Requirement (Mandatory) Proven experience implementing Data Masking as part of Data Migration and ETL/ELT execution in Enterprise Data Hub (EDH) environments. Hands-on experience masking sensitive data during data movement between source systems, SQL Server, Snowflake, Databricks, and downstream reporting platforms. Experience designing and implementing enterprise data masking strategies for PII, PHI, PCI, and other sensitive business data. Experience integrating masking controls into ETL pipelines while maintaining data quality, integrity, and regulatory compliance. Strong understanding of data governance, security, and compliance requirements throughout migration and transformation processes. --- Key Responsibilities Data Masking & Data Migration (Primary Responsibility) Design and implement enterprise Data Masking solutions during Data Migration and ETL/ELT execution. Develop masking strategies for sensitive data across Enterprise Data Hub (EDH) platforms. Ensure secure migration of confidential data while preserving referential integrity and business usability. Integrate masking logic into Azure Data Factory (ADF) pipelines and automated ETL frameworks. Validate masked datasets and ensure compliance with organizational security standards. Collaborate with business, security, and data governance teams to define masking rules and policies. SQL Server & Azure Data Engineering Design and implement SQL Server Dynamic Data Masking (DDM) solutions. Develop and maintain Azure Data Factory (ADF) pipeline frameworks for data ingestion and transformation. Execute and automate Golden Copy data refreshes across Enterprise Data Hub (EDH) and Anchor SQL Server environments. Optimize SQL Server databases for performance, scalability, and reliability. Automate deployment, monitoring, and maintenance of ETL/ELT processes. Snowflake & Databricks Implement column-level security and masking policies in Snowflake and Databricks. Develop and maintain materialized masked views for secure data access. Build schema drift monitoring and automated alerting solutions. Implement enterprise data governance, access controls, and compliance standards. Collaborate with architects and business stakeholders to deliver secure, scalable cloud data solutions. General Responsibilities Design scalable, reusable, metadata-driven data pipeline frameworks. Troubleshoot production issues and optimize ETL workflows. Create and maintain technical documentation. Participate in Agile ceremonies and collaborate with distributed teams. Communicate effectively with US-based stakeholders and provide regular project updates. --- Required Skills (Mandatory) 6+ years of experience in Data Engineering. Demonstrated experience implementing Data Masking during Data Migration and ETL/ELT execution (Mandatory). Experience working in Enterprise Data Hub (EDH) environments. Strong expertise in Microsoft SQL Server and T-SQL. Hands-on experience with SQL Server Dynamic Data Masking (DDM). Strong experience with Azure Data Factory (ADF). Experience with enterprise data migration and data transformation projects. Strong knowledge of Snowflake and Databricks. Experience implementing column-level security and masking policies. Experience creating materialized masked views. Experience with schema drift monitoring and metadata-driven ETL frameworks. Strong understanding of data governance, data security, and regulatory compliance. Experience with ETL/ELT development and enterprise data warehousing. Familiarity with Git, CI/CD pipelines, and Agile methodologies. --- Preferred Skills Azure Data Lake Storage (ADLS) Azure Synapse Analytics PySpark Python Azure DevOps PowerShell Microsoft Purview or similar data governance tools --- Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. Strong analytical, troubleshooting, and communication skills. Experience working with global teams and US-based clients is highly preferred. --- Engagement Details Client: AIGREV (US Client) Location: Remote (India) Contract Duration: 6 Months Work Hours: Candidate should be flexible to work during overlapping US business hours. Start Date: Immediate or as per project requirement.

Project ID: 40561251