Lead Software Engineer
Key Skills for This Role
Full Job Posting
Key responsibilities
- Design, develop, and maintain robust, scalable pipelines using Azure Data Factory and Databricks.
- Implement batch and real-time ingestion using Confluent Kafka.
- Build and optimize data models, transformations, and ETL/ELT pipelines using SQL and Spark.
- Develop and manage Azure Data Lake Storage solutions.
- Ensure data quality, integrity, and governance; support integration with core banking and CRM systems.
- Optimize large-scale data performance, translate stakeholder requirements into solutions, and troubleshoot production issues.
- Ensure compliance with banking regulations and data privacy.
Required skills and experience
- Strong SQL expertise in complex queries, tuning, and modeling; hands-on Databricks, Spark, and PySpark experience.
- Experience with Confluent Kafka and event-driven architecture, Azure Data Factory, and Azure Data Lake Storage.
- Understanding of data warehousing concepts; familiarity with CI/CD and DevOps for data platforms.
- Bachelor’s or Master’s degree in a relevant field.
Domain knowledge and additional qualifications
- Banking or financial services experience is preferred; core banking, payments, lending, wealth management, and KYC/AML knowledge are relevant domain areas.
- Azure or data engineering certifications are preferred.
- Python or Scala, data governance tools, APIs and microservices, and Power BI are good to have.
- Strong analytical, problem-solving, communication, and stakeholder engagement skills; ability to work in fast-paced settings and collaborate with ownership.
Success indicators
Deliver scalable pipelines, improve data reliability, reduce data latency, and align delivery with business requirements.
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