Data Engineer

 Design, build, and maintain complex data solutions and ETL pipelines using Python, Spark, SQL, and AWS services (S3, Glue, Redshift, MWAA, EMR, Lambda)

• Develop high-quality data architecture and scalable pipelines to support customer reporting needs, while implementing and supporting analytics infrastructure for internal Finance customers

• Interface with technology teams to extract, transform, and load data from various sources, ensuring data quality and making appropriate trade-offs in design decisions

• Collaborate with business users, developers, and BI Engineers to deliver on data architecture projects and next-generation financial solutions

• Actively participate in code reviews, design discussions, and team planning, while continually improving reporting processes and automating self-service support

• Identify and implement process improvements to drive innovation, scale existing solutions, and create new ones based on stakeholder needs

• Diagnose and resolve operational issues through detailed root cause analysis, maintaining high standards of system availability and reliability


About the team
The Operations finance data ecosystem supports global data management solutions inclusive of the scaling solutions to support 10+ data producer teams and 2500 finance customers. The role will work with BIE/DE teams across the organization, identifying critical customer pain points and help design , implement and drive customer's data journey. In the age of AI capabilities, the role will identify newer mechanisms to help incorporate AI driven workflows both for our builder and customer communities.

Basic Qualifications

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Bachelor's degree
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Knowledge of distributed systems as it pertains to data storage and computing