Senior Software Engineer, Data Engineering

Chime Financial, Inc • San Francisco, CA

6h • $220,000 - $240,000 • Hybrid

About The Position

We are seeking a Senior Software Engineer, Data Engineering at Chime’s San Francisco, CA office. The base salary offered for this role will begin at $220,000 and up to $240,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. In this role, you can expect to 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. Ownership of 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. Some telecommuting is permitted.

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.
• 4 years of experience utilizing 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;
• 4 years of experience utilizing 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;
• 4 years of experience utilizing knowledge of Extract Transform and Load (ETL) to process both structured and semi-structured data;
• 4 years of experience utilizing knowledge of orchestration tools such as Airflow and shell scripting for automating pipelines.
• 1 year of experience utilizing knowledge of data warehousing concepts and MPP databases to create data warehouse for processing and storing large volumes of data;
• 1 year of experience utilizing knowledge of Data Modeling concepts, Lucid Chart and Erwin Data Modeler to create data model for enterprise applications;
• 1 year of experience utilizing knowledge of SQL for data extraction, manipulation and analysis across large datasets;
• 1 year of experience utilizing knowledge of Python scripting and libraries including NumPy and Pandas to create and automate data Pipelines, for data extraction, manipulation, and data analysis;
• 1 year of experience utilizing knowledge of Data Visualization tools such as AWS Quicksight and Tableau to create dashboards and generate insights;
• 1 year of experience with working with stakeholders for providing business insights.

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.
• Ownership of 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.

Benefits

• bonus
• competitive equity package
• backup child, elder, and/or pet care
• subsidized commuter benefit
• 401k match
• medical benefits
• dental benefits
• vision benefits
• life benefits
• disability benefits
• Generous vacation policy
• company-wide Chime Days
• company-wide paid days off
• 1% of your time off to support local community organizations
• Annual wellness stipend
• Up to 24 weeks of paid parental leave for birthing parents
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior