About the job
We are seeking a skilled data engineer to design, develop, and maintain robust and scalable data pipelines. The successful candidate will work with Azure Data Factory and Databricks, implementing both batch and real-time data ingestion frameworks while ensuring high data quality and compliance with banking regulations.
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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
- 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
- Bachelor’s 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
