Confluent Data Engineer

Virtusa Hiring Confluent Data Engineers.

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

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 Master’s 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