Big Data Solutions Architect

Key Skills

Amazon RedShift, Amazon Simple Storage Service (S3), Apache Impala, AWS, Big Data Technology, Data Architecture, HBase, Machine learning techniques, MongoDB, MySQL, Postgres, Teradata

Job Description

Job Duties and Responsibilities

Key Responsibilities:

• Deploy enterprise-ready, secure, and compliant data-oriented solutions leveraging Data Warehouse, Big Data, and Machine Learning frameworks
• Optimizing data engineering and machine learning pipelines
• Reviews architectural designs to ensure consistency & alignment with defined target architecture and adherence to established architecture standards
• Support data and cloud transformation initiatives
• 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 point and strategic solutions
• Assist solution providers with the definition and implementation of technical and business strategies

Skills, Experience and Requirements

Education and Experience:

• Bachelor's Degree in a technical field and 12+ years of experience
• Experience in AWS cloud transformation projects is required
• Should have prior experience in working as a Data Warehouse/Big Data Architect
• Experience in advanced Apache Spark processing framework, and spark programming languages such as Scala/Python/Advanced Java with sound knowledge in shell scripting
• Experience in AWS services such as EMR, Glue, S3, Athena, DynamoDB, IAM, Lambda, Cloudwatch, and Data Pipeline
• Experience in writing spark streaming jobs (producers/consumers) using Apache Kafka or AWS Kinesis is required
• Experience in logical & physical table design in Big Data environments to suit processing frameworks
• Telecommunication experience is an added advantage

Skills and Qualifications:

• Should have experience in both functional programming and Spark SQL programming dealing with processing terabytes of data
• Specifically, this experience must be in writing Big Data data engineering jobs for large-scale data integration in AWS; prior experience in writing Machine Learning data pipelines using Spark programming language is an added advantage
• Advanced SQL experience including SQL performance tuning is a must
• Should have worked on other big data frameworks such as MapReduce, HDFS, Hive/Impala, AWS Athena
• Knowledge of using, setting up, and tuning resource management frameworks such as Yarn, Mesos, or standalone spark
• Knowledge in a variety of data platforms such as Redshift, S3, Teradata, Hbase, MySQL/Postgres, MongoDB
• Must have used the technologies for deploying specific solutions in the area of Big Data and Machine learning

Salary Ranges

Compensation: $127,050.00/Year - $208,725.00/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 provided is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level and competencies. Compensation is also based on the role's location and may change depending on the work location. Candidates must 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 and will continue to extend by 3 days until the position is filled.