Data Engineer

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Quick summary

Work type: On-site
Location: Austin, TX
Employment: Full-time
Posted: 5 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $168k

$116k $218k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $126,800–$208,293.

Based on 240 similar postings.

Employer

About Q2

Q2 Holdings is a cloud-based banking software company providing digital banking solutions to banks, credit unions, and alternative financial companies, including consumer and business banking platforms. Industry: Financial Technology & Digital Banking

Q2 currently has 43 open roles on FindRole.

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At a glance

TL;DR · Data Engineer

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JOB TITLE: Data Engineer The Data Engineer joins the Risk & Fraud team to design, implement, test, and operate cloud-native, data-driven services and applications across the Fraud Intelligence Platform. This production-focused role involves building reliable software in environments where quality and correctness are paramount. The successful candidate will manage data transformations, orchestration, pipelines, and replication to help customers proactively manage business risks and fraud. Key technical requirements include proficiency with SQL and NoSQL databases, data warehouses, and distributed file storage. The role utilizes a diverse tech stack including Apache Airflow, dbt, Kafka, Snowflake, SQL Server, Postgres, DynamoDB, Python, C#, Golang, Bash, GitLab, Azure DevOps, Terraform, Argo CD, Kubernetes, Docker, Pyspark, Snowpark, AWS Glue, Pandas, Databricks, and SageMaker.

What does a Data Engineer earn?

Median $159000 from 203 postings across 58 companies.

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Skills

Python C# Golang SQL NoSQL Apache Airflow dbt Kafka Snowflake SQL Server DynamoDB Terraform Kubernetes Docker GitLab Azure DevOps Argo CD Pyspark Snowpark AWS Glue Pandas Databricks SageMaker CI/CD

What you'll do

Design, implement, test, and operate cloud-native, data-driven services and applications.
Build and enhance products for the Fraud Intelligence Platform to combat fraud.
Develop and manage data transformations, orchestration, and pipelines using tools like Airflow and dbt.
Manage data movement and replication across various databases and distributed file storage.
Maintain and operate production systems using SQL, NoSQL, and data warehouses like Snowflake.
Deploy and manage infrastructure using CI/CD tools, Terraform, Kubernetes, and Docker.
Build reliable software across the full stack in high-quality, data-centric environments.

What we're looking for

A Bachelor’s degree in Computer Science, Information Systems, or a similar field.
A minimum of 2 years of related work experience.
An advanced degree in a relevant field.
Working knowledge of data transformations, data orchestration, pipelines, and data replication.
Working knowledge of SQL and NoSQL databases, data warehouses, distributed file storage, and compute platforms.
Good understanding of software engineering, distributed software design, and data-centric systems architecture.
Proficiency with tools including Apache Airflow, dbt, Kafka, Snowflake, SQL Server, Postgres, DynamoDB, Python, C#, Golang, Bash, GitLab, Azure DevOps, Terraform, Argo CD, Kubernetes, Docker, Pyspark, Snowpark, AWS Glue, Pandas, Databricks, and SageMaker.
Authorization to work for any employer in the U.S.