Data Engineer for Cloud Computing
2 days ago
About the Role
We are seeking an experienced Data Engineer for Cloud Computing to join our team at DISH. As a key member of our technology team, you will be responsible for designing, building, and maintaining large-scale data processing systems in the cloud.
Key Responsibilities:
- Leverage big data processing frameworks to create and optimize data engineering pipelines for analytics projects.
- Support data and cloud transformation initiatives across various departments.
- Collaborate with software engineers and data scientists to deliver high-quality data-driven solutions.
- Contribute to the development of our cloud strategy based on prior experience and industry trends.
- Stay up-to-date with the latest technologies in the rapidly evolving field of big data engineering.
Requirements:
- 6-12 years of experience in Big Data Engineering/Data Analysis, preferably from a Data Warehouse/Big Data background.
- Advanced Apache Spark processing framework skills, including Scala/Python/Java programming languages and shell scripting.
- Experience working with Core Spark, Spark Streaming, DataFrame API, Data Set API, RDD APIs, and Spark SQL programming, handling terabytes of data.
- Strong knowledge of SQL performance tuning using Hive/Impala frameworks.
- Familiarity with ElasticSearch (OpenSearch) and Kibana Dashboards, as well as experience with Apache Kafka or AWS Kinesis streaming frameworks.
- Able to create and maintain automated ETL processes with focus on data flow, error recovery, and exception handling.
- Knowledge of resource management frameworks like standalone Spark, Yarn, or Mesos.
- Experience with physical table design in Big Data environments.
- Familiarity with external job schedulers such as autosys, aws data pipeline, airflow, etc.
- Experience working with Key/Value data stores like Hbase.
- AWS services expertise, including EMR, Glue, S3, Athena, IAM, Lambda, and CloudWatch.
Estimated Salary Range: $96,250 - $137,500 per year.
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