Senior Data Engineer

DISH Network Technologies India Pvt. Ltd is a technology subsidiary of EchoStar. Our organization is at the forefront of technology, serving as a disruptive force and driving innovation and value on behalf of our customers.

Our product portfolio includes Boost Mobile (consumer wireless), DISH TV (direct broadcast satellite), Sling TV (over-the-top service provider), Hughes (global satellite connectivity solutions) and Hughesnet (satellite internet).

Our facilities in India are some of EchoStar's largest development centers outside the U.S. As a hub for technological convergence, our engineering talent is a catalyst for innovation in multimedia network and communications development.

EchoStar does not charge any fees to job applicants or candidates at any point during the recruitment and hiring process. We strongly advise all individuals to be vigilant and disregard any unsolicited requests for payment or personal financial information related to an EchoStar employment opportunity.

Our Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our people play vital roles in connecting consumers with the products and platforms of tomorrow.

• →Evangelist for data engineering function leveraging big data processing framework.
• →Creation and optimization of data engineering pipelines for analytics projects.
• →Support data and cloud transformation initiatives
• →Support our software engineers and data scientists
• →Contribute to our cloud strategy based on prior experience
• →Understand the latest technologies in a rapidly innovative marketplace
• →Independently work with all stakeholders across the organization to deliver enhanced functionality

• Expereince of 5+ years in Big data with engineering background
• Experience in advanced Apache Spark processing framework, spark programming languages such as Scala/Python with sound knowledge in shell scripting.
• Advanced SQL experience including SQL performance tuning
• Experience in writing spark streaming jobs integrating with streaming frameworks such as Apache Kafka or AWS Kinesis.
• Create and maintain automated ETL processes with special focus on data flow, error recovery, and exception handling and reporting
• Gather and understand data requirements, work in the team to achieve high quality data ingestion and build systems that can process the data, transform the data
• Experience working with external job schedulers such as Airflow etc.
• Experience in AWS services such as EMR, Glue (server less architecture), S3, Athena, IAM, Lambda and Cloud watch is required.