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Big Data Solutions Architect

Littleton, CO, United States

Company Summary DISH, an EchoStar Company, has been reimagining the future of connectivity for more than 40 years. Our business reach spans satellite television service, live-streaming and on-demand programming, smart home installation services, mobile plans and products, and now we are building America’s First Smart Network™.

Today, our brands include EchoStar, Hughes, DISH TV, Sling TV, Boost Infinite, Boost Mobile, DISH Wireless, OnTech and GenMobile.

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 Key Responsibilities:

Deploy enterprise-ready, secure, and compliant data-oriented solutions leveraging Data Warehouse, Big Data, and Machine Learning frameworks

Optimizing data engineering and machine learning pipelines

Reviews architectural designs to ensure consistency & alignment with defined target architecture and adherence to established architecture standards

Support data and cloud transformation initiatives

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 point and strategic solutions

Assist solution providers with the definition and implementation of technical and business strategies

Skills, Experience and Requirements Education and Experience:

Bachelor's Degree in a technical field and 12+ years of experience

Experience in AWS cloud transformation projects is required

Should have prior experience in working as a Data Warehouse/Big Data Architect

Experience in advanced Apache Spark processing framework, and spark programming languages such as Scala/Python/Advanced Java with sound knowledge in shell scripting

Experience in AWS services such as EMR, Glue, S3, Athena, DynamoDB, IAM, Lambda, Cloudwatch, and Data Pipeline

Experience in writing spark streaming jobs (producers/consumers) using Apache Kafka or AWS Kinesis is required

Experience in logical & physical table design in Big Data environments to suit processing frameworks

Telecommunication experience is an added advantage

Skills and Qualifications:

Should have experience in both functional programming and 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; prior experience in writing Machine Learning data pipelines using Spark programming language is an added advantage

Advanced SQL experience including SQL performance tuning is a must

Should have worked on other big data frameworks such as MapReduce, HDFS, Hive/Impala, AWS Athena

Knowledge of using, setting up, and tuning resource management frameworks such as Yarn, Mesos, or standalone spark

Knowledge in a variety of data platforms such as Redshift, S3, Teradata, Hbase, MySQL/Postgres, MongoDB

Must have used the technologies for deploying specific solutions in the area of Big Data and Machine learning

#LI-CH2

Salary Ranges

Compensation: $127,050.00/Year - $208,725.00/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: DISH Benefits. The base pay range provided is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level and competencies. Compensation is also based on the role's location and may change depending on the work location. Candidates must successfully complete a pre-employment screen, which may include a drug test and DMV check. The posting will be active for a minimum of 3 days and will continue to extend by 3 days until the position is filled.

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