DISH Network Technologies India Pvt. Ltd is a technology subsidiary of EchoStar Corporation. 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), Boost Mobile Network (5G connectivity), DISH TV (Direct Broadcast Satellite), Sling TV (Over The Top service provider), OnTech (smart home services), 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.
Department Summary
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.
Job Duties and Responsibilities
- Create, architect and optimize data engineering pipelines for analytics projects
- Review architectural designs to ensure consistency and alignment with defined target architecture and adherence to established architecture standards
- Evangelist for data engineering function leveraging Big data processing framework
- Support data and cloud transformation initiatives
- Independently work with all stakeholders across the organization to deliver enhanced functionality
- Work with PO/business to collect requirements and guide the teams for delivery
- Ready to work extended hours to provide adequate overlap with onshore teams
- Mentor junior team members
Skills, Experience and Requirements
- Must be from data engineering - background with 10+ years of experience
- Experience in Apache Spark processing framework, spark programming languages such as Scala/Python
- Experience in working with Core Spark, Spark Structured Streaming, Data Frame API, Data set API, RDD APIs & Spark SQL programming dealing with processing terabytes of data. Specifically, this experience must be in writing "Big Data'' data engineering jobs for large scale data integration in AWS.
- Experience in writing spark streaming jobs integrating with streaming frameworks such as Apache Kafka
- Experience working with external job schedulers such as autosys, aws data pipeline, airflow etc.
- Experience in AWS services such as EMR, Glue, S3, Athena, IAM, Lambda and Cloud watch is required.
Benefits
- Insurance and Wellbeing
- Financial & Retiral Benefit Program
- Mental Wellbeing
- Employee Stock Purchase Program (ESPP)
- Professional Development Reimbursement
- Time Off
- Team Outings
