Sr. Data Engineer

Key Responsibilities Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines. Analyze, diagnose, and resolve DQCI (Data Quality & Critical Issues) remediation requirements across the data ecosystem. Implement fixes across ingestion, transformation, and consumption layers to ensure data accuracy and consistency. Perform root-cause analysis of data defects and implement sustainable long-term solutions. Develop and optimize ETL/ELT processes using industry-leading data integration tools. Build and enhance data pipelines to support business intelligence, reporting, analytics, and downstream applications. Develop complex data transformation and mapping logic to meet business requirements. Integrate data from multiple internal and external systems through APIs and batch interfaces. Optimize SQL queries, database objects, and data processing workloads for performance and scalability. Collaborate with business, analytics, and architecture teams to ensure high-quality data delivery. Support DevOps and CI/CD practices for deployment, version control, and release management. Ensure adherence to data governance, security, and compliance standards. Required Technical Skills Core Skills Snowflake Development Data modeling and schema design Performance tuning and optimization Stored procedures, tasks, streams Matillion ETL/ELT Job orchestration Data transformation and workflow development Integration with Snowflake and cloud platforms Talend Data Integration ETL development Data migration and integration solutions Data quality and validation frameworks Advanced SQL Complex joins, stored procedures, views, and performance optimization Query tuning and large-scale data processing Data Pipelines Batch and near real-time processing pipelines Data ingestion, transformation, and orchestration Data Transformation & Mapping Source-to-target mappings Business rule implementation Data reconciliation API Integration REST/SOAP APIs API-based data ingestion and integration Azure DevOps Source control management CI/CD pipeline and deployment Release management and automation Expected Contributions Diagnose and resolve DQCI remediation work across enterprise data platforms. Implement fixes across ingestion and transformation pipelines to eliminate recurring data issues. Correct defects at source, integration, or consumption layers based on root-cause analysis. Improve overall platform stability, reliability, and data quality. Deliver sustainable and scalable fixes rather than temporary workarounds. Optimize existing ETL/ELT processes and improve pipeline performance. Support production issues and provide timely resolution of critical data incidents. Ensure data accuracy, completeness, and consistency across systems. Collaborate effectively with Data Architects, Business Analysts, QA teams, and stakeholders. Contribute to continuous improvement initiatives and engineering best practices. Preferred Qualifications Strong Experience with Talend + Snowflake + Matillion + Postgress Hands on experience on AWS and S3 Strong knowledge of data warehousing concepts, dimensional modeling, and data governance. Experience working in Data warehousing projects & agile Strong analytical, troubleshooting, and problem-solving skills. Target Designation: Senior Data Engineer Location Preference: Offshore Primary Skills: Talend, Snowflake, Advanced SQL, Matillion, Data Pipeline Engineering, Data warehousing. Secondary Skills: Postgress, API integration, AWS, Matillion, Azure DevOps Role Summary We are looking for an experienced Senior Data Engineer with strong expertise in modern data engineering, data integration, and cloud-based data platforms. The resource will be responsible for diagnosing and resolving data quality and critical integration issues, implementing sustainable fixes across data pipelines, and ensuring reliable data delivery across enterprise systems. OK OK