Senior Confluent Data Engineer

Virtusa Hiring Confluent Data Engineers.

If interested pls share details and updated cv on [email protected]

Total Exp:

Confluent Kafka Exp:

Data Engineer Exp:

Current CTC:

Expected CTC:

Current Company:

Last working day:

Current Location:

Preferred Location:

JD:

Key Responsibilities

• Design, develop, and maintain robust, scalable data pipelines using Azure Data Factory

(ADF) and Databricks

• Implement batch and real-time data ingestion frameworks leveraging Confluent Kafka
• Build and optimize data models, transformations, and ETL/ELT pipelines using SQL and

Spark

• Develop and manage data storage solutions in Azure Data Lake Storage (ADLS)
• Ensure high data quality, integrity, and governance standards
• Support data integration across systems including core banking and CRM
• Optimize performance of large-scale datasets
• Collaborate with stakeholders to translate requirements into solutions
• Ensure compliance with banking regulations and data privacy
• Troubleshoot production issues

Required Skills & Experience

• Strong expertise in SQL (complex queries, tuning, modeling)
• Hands-on experience with Databricks, Spark, PySpark
• Experience with Confluent Kafka and event-driven architecture
• Experience with Azure Data Factory (ADF)
• Experience with Azure Data Lake Storage (ADLS)
• Understanding of data warehousing concepts
• Familiarity with CI/CD and DevOps for data platforms

Domain Knowledge (Preferred)

• Experience in banking or financial services

Classification: RAKBANK-Internal

• Understanding of core banking systems
• Knowledge of payments, lending, wealth management
• Awareness of regulatory frameworks (KYC, AML)

Soft Skills

• Strong analytical and problem-solving skills
• Excellent communication and stakeholder engagement
• Ability to work in fast-paced environments
• Strong ownership and collaboration mindset

Qualifications

• Bachelors or Masters degree in relevant field
• Azure/Data engineering certifications preferred

Good to Have

• Experience with Python or Scala
• Exposure to data governance tools
• Knowledge of APIs and microservices
• Experience with BI tools like Power BI

Key Success Indicators

• Delivery of scalable pipelines
• Improved data reliability
• Reduced data latency
• Alignment with business requirements