Sr. Data Engineer

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

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