Data Engineer II: Airflow & AI-Driven Pipelines on AWS

EchoStar; Englewood (CO); On-site; USD 83,000 - 119,000; Full time

Benefits offered by this job

Health perks

401(k) match

HSA

ESPP

Flexible time off

Job summary

EchoStar in Colorado is seeking a data engineering professional to design and optimize high-performance data pipelines for batch and streaming workloads. You will drive PoC projects evaluating Airflow as an enterprise orchestration tool and integrate Generative AI tools to improve data quality and automation.

You will work with Python, PySpark, SQL, and AWS EMR, building scalable cloud-based infrastructure while ensuring governance, security, and cost efficiency across the data lifecycle.

Qualifications

• Bachelor's degree in CS, data engineering, or related field
• At least 2 years of experience in Big Data and data engineering
• Experience with Python and SQL, EMR and Spark, Airflow or Control-M, GitLab CI/CD, and Amazon Q or Generative AI tools

Responsibilities

• Construct and optimize scalable data pipelines for batch and streaming data from multiple sources
• Develop data processing jobs using Spark on Amazon EMR with attention to performance and cost
• Implement transformation logic using Python, PySpark, and SQL
• Lead PoC projects evaluating Apache Airflow for enterprise orchestration and DAG design
• Explore integration points for Amazon Q to enable data quality checks and documentation
• Implement CI/CD pipelines for data platform components using GitLab and IaC tools

Skills

Python

PySpark

SQL

Big Data

Education

Bachelor's degree in Computer Science or Data Engineering

Tools

Amazon EMR

EC2

S3

Apache Airflow

Control-M

GitLab CI/CD

Terraform

AWS CloudFormation

Amazon Q

Job description

EchoStar in Colorado is seeking a data engineering professional to design and optimize high-performance data pipelines for batch and streaming workloads. You will drive PoC projects evaluating Airflow as an enterprise orchestration tool and integrate Generative AI tools to improve data quality and automation.

You will work with Python, PySpark, SQL, and AWS EMR, building scalable cloud-based infrastructure while ensuring governance, security, and cost efficiency across the data lifecycle.