Job Duties and Responsibilities

Candidates must be willing to participate in at least one in-person interview.

Managing and scaling distributed data architectures while maintaining cloud cost-efficiency represents a major modern operational challenge. This role directly addresses these complexities by leading the development, deployment, and optimization of robust cloud data platforms. By directing collaborative, cross-functional engineering teams across both on-site and offshore locations, the manager ensures stable real-time data flow and rapid issue resolution. This position is central to transforming raw business requirements into performant, automated data integration pipelines.

What Success Looks Like (Objectives):

• 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, Experience and Requirements

Core Skills and Competencies (What you'll bring):

• Critical experience designing and building large-scale distributed big data pipelines
• Proven leadership managing and coordinating multi-site and offshore production support operations
• Strong technical capability in developing ingestion and curation pipelines using Databricks
• Proficiency in software engineering principles using Spark, Python, or Scala
• Deep understanding of database management systems, version control, and CI/CD concepts
• Practical AI application skills to automate and optimize data management tasks

Additional Qualifications:

• Experience with change data capture tools such as Qlik or Goldengate
• Familiarity with scheduling tools such as Control-M, Airflow, or AWS Step Functions
• Knowledge of Infrastructure-as-Code using Terraform or AWS CloudFormation

Minimum Requirements:

• Minimum Education: Bachelor's Degree in Computer Science, Information Technology, or a related field
• Minimum Experience: 5 years of experience in distributed data engineering; 3 years of experience leading on-site or offshore teams
• Required Technical Skills: Must have at least 2 years of experience with:
• AWS cloud infrastructure optimization
• Spark, Python, or Scala programming
• Kafka, Apache Flink, or real-time streaming tools
• Git and GitLab version control pipelines

Salary Ranges

Compensation: $127,050.00/Year - $181,500.00/Year
Benefits

We offer versatile health perks, including flexible spending accounts, HSA, a 401(k) Plan with company match, ESPP, career opportunities, and a flexible time away plan; all benefits can be viewed here: EchoStar Benefits.

The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level, and competencies; compensation is based on the role's location and is subject to change based on work location.

The posting will be active for a minimum of 3 days. The active posting will continue to extend by 3 days until the position is filled.