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 Mobile and Gen Mobile. 

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:

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

Skills, Experience and Requirements:

Education and Experience:

Must have 6-12 years of experience in Big Data Engineering/Data Analysis

Must be from a Data Warehouse/Big Data background

Skills and Qualifications:

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

Experience in working with Core Spark, Spark Streaming, DataFrame API, Data Set API, RDD APIs & Spark SQL programming dealing with processing terabytes of data

Advanced SQL experience using Hive/Impala framework including SQL performance tuning

Experience with ElasticSearch (OpenSearch) and Kibana Dashboards

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

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

Experience in physical table design in Big Data environment

Experience working with external job schedulers such as autosys, aws data pipeline, airflow etc

Experience working in Key/Value data store such as Hbase

Experience in AWS services such as EMR, Glue (serverless architecture), S3, Athena, IAM, Lambda and CloudWatch

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: .

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. Candidates need to 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. The active posting will continue to extend by 3 days until the position is filled.

Salary Range:

USD $(phone number removed) - $(phone number removed) / Year