Big Data Engineer
4 days ago
DISH is a leading technology company that has been revolutionizing the future of connectivity for over 40 years. Our business spans across satellite television service, live-streaming, on-demand programming, smart home installation services, mobile plans and products, and now we are building America's First Smart Network.
We have a diverse portfolio of brands, including EchoStar, Hughes, DISH TV, Sling TV, Boost Mobile, and Gen Mobile.
About the RoleWe are seeking a highly skilled Big Data Engineer to join our Technology team. As a Big Data Engineer, you will play a vital role in connecting consumers with the products and platforms of tomorrow.
Key Responsibilities:- Evangelize the data engineering function, leveraging big data processing frameworks.
- Create and optimize data engineering pipelines for analytics projects.
- Support data and cloud transformation initiatives.
- Collaborate with software engineers and data scientists to deliver enhanced functionality.
- Contribute to our cloud strategy based on prior experience.
- Stay up-to-date with the latest technologies in a rapidly innovative marketplace.
- Independently work with stakeholders across the organization to deliver results.
- 6-12 years of experience in Big Data Engineering/Data Analysis.
- 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.
- 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.
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