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EchoStar

Big Data Engineer

Reposted Yesterday
In-Office
Littleton, CO
Senior level
In-Office
Littleton, CO
Senior level
Design, build, and manage data pipelines for AI models; ensure high-quality data availability, perform data cleaning and transformation, and collaborate with stakeholders.
The summary above was generated by AI
Company Summary
EchoStar is reimagining the future of connectivity. Our business reach spans satellite television service, live-streaming and on-demand programming, smart home installation services, mobile plans and products.
Today, our brands include Boost Mobile, DISH TV, Gen Mobile, Hughes and Sling TV.
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
Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.
As a Big Data Engineer on our 5G Network Analytics team, you will be responsible for designing, building and managing data pipelines specifically tailored for artificial intelligence (AI) models.
Priorities include ensuring high-quality data is readily available for training and deployment, data cleaning, transformation, integration, quality checks, and collaborating with AI engineers to optimize model performance.
Key responsibilities of an AI data engineer:
  • Design and implement robust data pipelines to extract, transform, and load (ETL) data from various sources, optimizing for efficient AI model training.
  • Gather and understand data requirements, create and maintain automated ETL processes with special focus on data flow, error recovery, and exception handling and reporting
  • Support data and cloud transformation initiatives
  • Support our software engineers and data scientists
  • Understand the latest technologies in a rapidly innovative marketplace
  • Ability to work independently and with a team with all stakeholders across the organization to deliver enhanced functionality

Skills, Experience and Requirements
Education and Experience:
  • Bachelor's degree in computer science, or similar technical field
  • Minimum 5 years of experience in Big Data Engineering/Data Analysis

Preferred Skills and Qualifications:
  • Proficiency in Python, SQL and Apache Spark
  • AWS services such as EMR, Glue (serverless architecture), S3, Athena, IAM, Lambda and CloudWatch
  • Core Spark, Spark Streaming, DataFrame API, Data Set API, RDD APIs & Spark SQL programming dealing with processing terabytes of data
  • Advanced SQL using Hive/Impala framework including SQL performance tuning
  • Expertise in Hadoop, and other distributed computing frameworks
  • ElasticSearch (OpenSearch) and Kibana Dashboards
  • Resource management frameworks such as Yarn or Mesos.
  • Physical table design in Big Data environment
  • External job schedulers such as autosys, AWS data pipeline, airflow etc.
  • Experience working in Key/Value data store such as Hbase

Salary Ranges
Compensation: $96,250.00/Year - $137,500.00/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 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.

Top Skills

Airflow
Spark
Autosys
Aws Athena
Aws Cloudwatch
Aws Emr
Aws Glue
Aws Iam
Aws Lambda
Aws S3
Elasticsearch
Hadoop
Hbase
Hive
Impala
Kibana
Mesos
Python
SQL
Yarn

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