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
OK
OK