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As a Data Engineer, you will be a key contributor in building the Data Platform as a foundation for Data Analytics and AI.
Responsibilities:
- Design, develop, and maintain data pipelines and backend services for real-time decisioning, reporting, data collecting, and related functions.
- Data Requirements and Modeling
- Data Management and Transformation
- Produce high-quality, well-tested, and secure code.
- Develop and maintain software designed to improve data governance and security.
- Develop processes designed to ensure Data Security and Data Quality.
Requirements:
- BS/MS in Computer Science, Data Analytics, Data Management, Information Systems or related technical field or equivalent training & experience.
- 2+ years Incorporating data processing and workflow management tools into pipeline design.
- 2+ years’ experience in ETL/ELT, Data warehousing, and/ or Business Intelligence Development.
- 2+ years building and maintaining end-to-end data systems and supporting services in Python, Scala or similar.
- 2+ years using SQL to understand data and to investigate data issues or problems and provide solutions.
- Experience working in Banking/Financial Services industries
- Experience working with large data sets in SQL/Databricks/PySpark.
- Experience with Spark Streaming, and Delta (Live) Tables.
- Experience with storage systems such as Azure Storage/ Data Lakes.
- Experience developing on cloud platforms (preferably Azure) in a continuous delivery environment.
- Experience with microservices platforms (Kubernetes, Docker)
- Experience with Event-Driven streaming systems (Kafka, Event Hub, Event Grid, Apache Flink).
- Knowledge and use of DBT.
- Experience with data vault is a plus.
- Experience with Microsoft Fabric.
- 2+ years software development using languages like JavaScript, Java, or C#.
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