Senior Data Platform Lead - Cloud, Big Data & AI Ops

Dish Network Corporation; Englewood (CO); On-site; USD 127,050 - 181,500; Full time

Benefits offered by this job

Health perks

401(k) Plan with company match

ESPP

Flexible time away

Job summary

EchoStar seeks a senior data engineering leader to design, build and scale distributed data pipelines across cloud platforms. You will guide cross‑functional teams, oversee offshore collaboration, and optimize data architectures for real‑time insights.

You will drive Databricks workloads, implement robust CI/CD, and leverage AI for data quality and anomaly detection, while aligning with product goals and cost efficiency.

Qualifications

• Bachelor’s degree in CS/IT or related field.
• 5 years of distributed data engineering; 3 years leading on-site or offshore teams.
• 2+ years of AWS cloud optimization; Spark, Python or Scala; Kafka or Flink; Git/GitLab pipelines.

Responsibilities

• Lead the operations and delivery of big data solutions using modern cloud data platforms.
• Manage day-to-day development activities for new data solutions and troubleshoot existing production implementations.
• Coordinate with product owners and technical leads to resolve architectural and integration issues.
• Optimize AWS and data warehouse configurations to improve performance and reduce operational cloud spend.
• Design and implement automated CI/CD pipelines to streamline code deployments and pipeline reliability.
• Integrate AI-driven operations tools to automate anomaly detection and predictive data quality checks.

Skills

Big data pipelines

Leadership

Databricks

Spark

Python/Scala

CI/CD pipelines

AI integration

Kafka

Education

Bachelor's Degree in CS/IT or related

Tools

Terraform

AWS CloudFormation

Control-M

Airflow

AWS Step Functions

Qlik

GoldenGate

GitLab

Job description

EchoStar seeks a senior data engineering leader to design, build and scale distributed data pipelines across cloud platforms. You will guide cross‑functional teams, oversee offshore collaboration, and optimize data architectures for real‑time insights.

You will drive Databricks workloads, implement robust CI/CD, and leverage AI for data quality and anomaly detection, while aligning with product goals and cost efficiency.