Senior Software Engineer, Data Engineering

Chime

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: San Francisco, CA
Posted: 141 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $170k

$107k most similar roles pay here $238k

This listing doesn't post a salary. Most similar roles pay $149,500–$190,375.

Based on 240 similar postings.

Employer

About Chime

Chime is a financial technology company offering mobile-first banking services including fee-free checking accounts, savings accounts, and a secured credit builder card through partner banks. Industry: Financial Technology & Neobanking

Chime currently has 35 open roles on FindRole.

Most-posted roles

View all roles at Chime

At a glance

TL;DR · Senior Software Engineer, Data Engineering

Role Posting Log in to save

As a Senior Software Engineer, Data Engineering, you will join the data engineering team to build scalable data artifacts and insights that enable accurate, governed, data-driven decision-making. You will serve as a hands-on engineer responsible for building, scaling, and optimizing ETL pipelines while designing schemas capable of handling significant growth. Your daily work involves owning all aspects of data, including quality, governance, security, and the development of standardized models to support self-serve insights using AI. To succeed, you must possess expertise in SQL, Spark, AWS Glue, EMR, Airflow, and Python, along with experience in MPP database systems like Snowflake, AWS Redshift, or Teradata. You will collaborate with Data Science, Analytics, and DevOps teams to solve complex problems within the fintech industry by creating robust workflows that may become industry standards.

What does a Software Engineer earn in California?

Median $214000 from 775 postings across 63 companies.

See salary data

Skills

SQL Spark AWS Glue EMR Airflow Python Snowflake AWS Redshift Teradata ETL Data Governance MPP AI

What you'll do

Build, scale, and optimize production-quality ETL pipelines.
Design data schemas and architectures capable of handling significant data growth.
Manage all aspects of data including quality, governance, security, and schema design.
Develop standardized data models to enable self-serve insights using AI.
Ensure ETL workflows meet strict data quality and availability requirements.
Provide business insights by transforming raw data into governed, lucid datasets.
Monitor key metrics for data pipelines and provide visibility to partner teams.
Participate in an on-call rotation to respond to incidents outside of regular hours.

What we're looking for

5+ years of experience transforming data into governed and lucid datasets.
5+ years of hands-on experience building and deploying production-quality data pipelines.
5+ years of experience working with stakeholders to provide business insights.
5+ years of experience writing SQL, Spark, AWS Glue, EMR, Airflow, and Python.
3+ years of hands-on experience using MPP database systems like Snowflake, AWS Redshift, or Teradata.
Proven track record of successful partnerships with Analytics, Data Science, and DevOps teams.
Ability to monitor key metrics for data pipelines and build solutions for visibility.
Willingness to participate in an on-call rotation to respond to incidents outside regular hours.

Save