Data Engineer: Build Scalable Pipelines & Lakehouse

Sonatype Inc; Abbeyville (CO); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Parental leave

Diversity and inclusion working groups

Flexible working practices

Job summary

Sonatype is seeking a data engineer to build and maintain reliable data pipelines and ETL/ELT workflows. You will develop analytics-focused data models and collaborate with teammates to deliver clean, trusted datasets.

The role supports core data platform tools such as Spark and AWS services, and you’ll monitor pipelines for quality, performance, and reliability while contributing to CI/CD and documentation. English communication is essential.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field or equivalent practical experience.
• 2–4 years of experience in data engineering or backend data-related role.
• Strong skills in Java, Scala, or another backend programming language.
• Python (PySpark/pandas) skills.
• Experience with SQL and distributed data systems (e.g., Spark, Kafka, SQS).
• Familiarity with NoSQL stores like Cassandra, HBase, or similar.
• Understanding of data modeling for analytics and reporting.
• Proficient in English with strong communication skills.

Responsibilities

• Build and maintain reliable data pipelines and ETL/ELT workflows.
• Develop and optimize data models for analytics and internal tools.
• Work with team members to deliver clean, trusted datasets.
• Support core data platform tools like Spark and AWS services (S3, SNS, SQS, ECS/Fargate, EMR).
• Monitor data pipelines for quality, performance, and reliability.
• Write clear documentation and contribute to test coverage and CI/CD processes.
• Help shape our data lakehouse architecture and platform roadmap.

Skills

Java/Scala

Python

SQL

NoSQL

Spark

Kafka

SQS

Data modeling

English

CI/CD

Education

Bachelor's degree in CS/Engineering or related

Tools

dbt

Databricks

Terraform

CloudFormation

Job description

Sonatype is seeking a data engineer to build and maintain reliable data pipelines and ETL/ELT workflows. You will develop analytics-focused data models and collaborate with teammates to deliver clean, trusted datasets.

The role supports core data platform tools such as Spark and AWS services, and you’ll monitor pipelines for quality, performance, and reliability while contributing to CI/CD and documentation. English communication is essential.