About the Role
We are seeking a Senior Software Engineer at Chime's San Francisco, CA office.
The base salary offered for this role will begin at $210,000 and up to $230,000. 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
- Research, design, and develop fintech software or specialized utility programs.ย
- Analyze user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis.ย
- Update software or enhance existing software capabilities.ย
- Build a scalable data platform and pipelines that caters to the data plumbing needs of Chime.ย
- Architect and build workflows that could potentially become de facto standards for the fintech industry.ย
- Be a hands-on engineer, building, scaling, and optimizing self-serve ETL frameworks that can handle streaming and/or batch processing. ย
- Own the ETL workflows and make sure the pipeline meets data quality and availability requirements.ย
- Work closely with other data engineering teams to integrate schema registry and establish data lineage for all data domains.ย
- Work closely with our stakeholder teams, like Data Science, Product Engineering, Analytics to help them with their data computation needs.ย
- Joint ownership of all aspects of data - data quality, data governance, data and schema design, data quality and security.ย
- Mentor and lead more junior engineers and help them improve their craft.
To thrive in this role, you must have
- Master's degree in Computer Science, Engineering or related field and 3 years of experience in the job offered or in a software engineer-related occupation.
- Position requires at least 1 year of experience in each of the following skills:
- Utilize knowledge of AWS/GCP to manage large-scale distributed data infrastructure, with a focus on debugging and resolving production issues through collaborative problem-solving;
- Utilize experience with optimizing data computation engines (e.g., Spark, Trino) to deliver high-performance queries and reduce latency;
- Utilize knowledge of containerization and orchestration technologies including Kubernetes and Docker to efficiently run the data platform infrastructure;
- Utilize experience with shadow testing, error investigation, and benchmark testing frameworks for high-quality data processing;
- Utilize experience with running production grade CI/CD systems to improve developer velocity and handle complicated rollbacks to improve system reliability;
- Utilize experience with designing fault-tolerant systems and implementing strategies to ensure high availability in distributed environments.
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