Senior Software Engineer, Data Engineering

Responsibilities

• Design strategies for enterprise databases, data warehouse systems, and multidimensional networks.
• Set standards for database operations, programming, query processes, and security.
• Model, design, and construct large relational databases or data warehouses.
• Create and optimize data models for warehouse infrastructure and workflow.
• Integrate new systems with existing warehouse structure and refine system performance and functionality.
• Build a scalable data platform that caters to the data plumbing needs of Chime.
• Build scalable data pipelines and frameworks.
• Architect and build workflows that could potentially become de facto standards for the fintech industry.
• Be a hands-on data engineer, building, scaling and optimizing ETL pipelines.
• Design data warehouse schemas and scale data warehouse process data for 10x data growth.
• Own all aspects of data - data quality, data governance, data and schema design, data quality and security.
• Own schema registry and dependency chart for persistent data.
• Own the ETL workflows and make sure the pipeline meets data quality and availability requirements.
• Work closely with partner teams, like Data Science, Analytics and DevOps.
• Transform data to governed and lucid datasets. Build and deploy production-quality data pipelines.
• Work with stakeholders to provide business insights.

Requirements

• Master’s degree in Computer Science, Information/Systems Engineering or related field and 4 years of experience in the job offered or in a software/data engineer-related occupation.
• At least 4 years of experience in each of the following:
  • Utilize knowledge of Distributed Computing and AWS Technologies such as AWS Glue, PySpark, and AWS EMR to create highly performant pipelines that can process the data at scale.
  • Utilize knowledge of modern Data Engineering concepts to create data lake using AWS Cloud technologies such as AWS EC2, AWS S3, AWS Lambda, AWS Spectrum, and AWS Glue.
  • Utilize knowledge of Extract Transform and Load (ETL) to process both structured and semi-structured data.
  • Utilize knowledge of orchestration tools such as Airflow and shell scripting for automating pipelines.
• At least 1 year of experience in each of the following:
  • Utilize knowledge of data warehousing concepts and MPP databases to create data warehouse for processing and storing large volumes of data.
  • Utilize knowledge of Data Modeling concepts, Lucid Chart and Erwin Data Modeler to create data model for enterprise applications.
  • Utilize knowledge of SQL for data extraction, manipulation and analysis across large datasets.
  • Utilize knowledge of Python scripting and libraries including NumPy and Pandas to create and automate data Pipelines, for data extraction, manipulation, and data analysis.
  • Utilize knowledge of Data Visualization tools such as AWS Quicksight and Tableau to create dashboards and generate insights.
  • Utilize experience with working with stakeholders for providing business insights.

Nice-to-Haves / Benefits

• Some telecommuting is permitted.
• Competitive salary based on experience.
• 401k match plus great medical, dental, vision, life, and disability benefits.
• Generous vacation policy and company-wide Chime Days, bonus company-wide paid days off.
• 1% of your time off to support local community organizations of your choice.
• Annual wellness stipend to use towards eligible wellness related expenses.
• Up to 24 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents.
• Access to Maven, a family planning tool, with $15k lifetime reimbursement for egg freezing, fertility treatments, adoption, and more.
• In-person and virtual events to connect with your fellow Chimers.