Senior Data Engineer: Pipelines, Spark & AWS (On-site)

Apex Systems; Greenwood Village (CO); Hybrid; USD 90,000 - 110,000; Full time

Job summary

Everforth Apex in Greenwood Village, CO is hiring a Data Engineer to design, build, and maintain scalable data pipelines and ETL/ELT workflows that power data science insights.

You will ingest data from diverse sources, monitor quality, and collaborate with the MLOps and analytics teams to deliver reliable, small-batch releases.

Strong Python and Scala skills, PySpark, SQL/NoSQL, and AWS experience are required, with a focus on performance, cost efficiency, and data reliability.

Qualifications

• Senior-level experience as a Data Engineer.
• Proficiency with PySpark and/or Spark.
• Strong programming skills in Python and Scala.
• Familiarity with cloud platforms such as AWS and related services.
• Proficiency with data orchestration tools like Airflow or AWS Step Functions.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Write and schedule jobs to ingest data from different sources.
• Ensure data quality and reliability by monitoring pipelines, validating schema changes, and setting up alerts for data anomalies.
• Optimize complex queries and data transformations for performance and cost efficiency.
• Collaborate with data scientists to gather requirements and validate output from jobs.
• Work closely with the MLOps team to support infrastructure and tooling changes.
• Deliver work at a steady, predictable pace to achieve commitments, release complete solutions in small batches, and identify and negotiate important tradeoffs.

Skills

Senior Data Engineer

Python

Scala

PySpark/Spark

SQL/NoSQL

Databricks

AWS

Data Pipelines

ETL/ELT

Tools

Airflow

AWS Step Functions

Job description

Everforth Apex in Greenwood Village, CO is hiring a Data Engineer to design, build, and maintain scalable data pipelines and ETL/ELT workflows that power data science insights.

You will ingest data from diverse sources, monitor quality, and collaborate with the MLOps and analytics teams to deliver reliable, small-batch releases.

Strong Python and Scala skills, PySpark, SQL/NoSQL, and AWS experience are required, with a focus on performance, cost efficiency, and data reliability.