Data Engineer

Required Skills:

• 5+ years of experience in building out data pipelines in Python or Java
• 2+ years of experience working in Azure Cloud Service
• Experience with data processing platform, such as Azure Data Factory
• Must be Fluent with SQL for data analysis
• Expertise with transactional database engines, such as SQL server
• Experience with data lake/data marts/data warehouse
• Must have Asset Management industry domain experience, ideally supporting Fixed Income products
• Excellent analytical and problem-solving skills with the ability to think quickly and offer alternatives both independently and within teams.
• Exposure working in an Agile environment with Scrum Master/Product owner and ability to deliver
• Ability to communicate the status and challenges with the team
• Demonstrating the ability to learn new skills and work as a team
• Experience with Spark
• Experience working in Hadoop or other Big data platforms
• Exposure to deploying code through pipeline
• Good exposure to Containers like ECS or Docker
• Working experience in a Linux based environment
• Direct experience supporting multiple business units for foundational data work and sound understanding of capital markets within Fixed Income
• Knowledge of Jira, Confluence, SAFe development methodology & DevOps
• Proven ability to work quickly in a dynamic environment.
• Bachelor's degree Computer Science or a related field.

 Responsibilities:

• Build and maintain new and existing applications in preparation for a large-scale architectural migration within an Agile function.
• Align with the Product Owner and Scrum Master in assessing business needs and transforming them into scalable applications.
• Build and maintain code to manage data received from heterogenous data formats including web-based sources, internal/external databases, flat files, heterogenous data formats (binary, ASCII).
• Help build new enterprise Datawarehouse and maintain the existing one.
• Design and support effective storage and retrieval of very large internal and external data set and be forward think about the convergence strategy with our cloud migration
• Assess the impact of scaling up and scaling out and ensure sustained data management and data delivery performance.
• Build interfaces for supporting evolving and new applications and accommodating new data sources and types of data.