Department Summary
DISH is a Fortune 200 company that continues to redefine the communications industry. Our legacy is innovation and a willingness to challenge the status quo, including reinventing ourselves. We disrupted the pay-TV industry in the mid-90s with the launch of the DISH satellite TV service, taking on some of the largest U.S. corporations in the process, and grew to be the fourth-largest pay-TV provider. We are doing it again with the first live, internet-delivered TV service - Sling TV - that bucks traditional pay-TV norms and gives consumers a truly new way to access and watch television.
Now we have our sights set on upending the wireless industry and unseating the entrenched incumbent carriers.
We are driven by curiosity, pride, adventure, and a desire to win - it's in our DNA. We're looking for people with boundless energy, intelligence, and an overwhelming need to achieve to join our team as we embark on the next chapter of our story. Opportunity is here. We are DISH.
Job Duties and Responsibilities
This role is located onsite in American Fork, UT or Englewood, CO
The Senior Big Data Engineer will be responsible for expanding our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler, who enjoys optimizing data systems and building them from the ground up.
This position will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
Essential Duties and Responsibilities

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet both functional and non-functional business requirements
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation and loading of data from a wide variety of data sources using SQL and AWS 'big data' technologies
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
• Collaborate with stakeholders including the executive, product, data and design teams to assist with data-related technical issues and support their data infrastructure needs
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader;
• Work with data and analytics experts to strive for greater functionality in our data systems.

Work Hours: Regular work/business hours
Work Attire - Business Casual
Skills, Experience and Requirements
Experience:

• Five or more years of experience working with distributed data technologies (e.g. Hadoop, MapReduce, Spark, Kafka, Flink, etc.) for building efficient, large-scale 'big data' pipelines
• Strong Software Engineering experience with proficiency in at least one of the following: programming languages: Golang, Java, Python, Scala or equivalent

Education:

• A Bachelor's or Master's degree in Computer Science or related technical field or equivalent practical experience

Knowledge, Skills, Abilities (KSA's):
Ideal qualifications:

• Implement data ingestion pipelines both real time and batch using best practices
• Experience with building stream-processing applications using Apache Flink, Kafka Streams or others
• Experience with Cloud Computing platforms like Amazon AWS, Google Cloud etc.
• Experience supporting and working with cross-functional teams in a dynamic environment
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with ELK stack.
• Ability to work in a Linux environment.
• Experience in building distributed, high-volume data services
• Experience with big data processing and analytics stack in AWS: EMR, S3, EC2, Athena, Kinesis, Lambda, Quicksight etc.
• Knowledge of data science tools and their integration with data lakes
• Experience in container technologies like Docker/Kubernetes

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Salary Range
Compensation: $125,000.00/Year - $162,500.00/Year
Benefits
From versatile health perks to new career opportunities, check out our benefits on our careers website . Successful completion of a pre-employment screen, to include a drug test and criminal background check.