Data Engineer

The Data Engineer works within the BI/Data Analytics team on critical reporting and analysis initiatives. Reporting spans from custom requests to scheduled jobs to supporting our growing data warehouse, and building our future cloud analytics platform. The developer must be able to communicate to business users the exact scope of metrics as well as the confidence and quality of the data in reports.

Department: Technology
Project Location(s): Las Vegas, NV, US
Education: Bachelors
Compensation: 100k+

Responsibilities

  • Work directly with the business users to understand the reporting needs and lead business users to practical solutions
  • Help translate business requirements into specification documents to track and perform analysis of new and existing site features
  • Understand the necessity of data quality and the requirement for the confidence of accuracy of any reports
  • Develop/monitor/maintain new reports, procedures, data structures and databases
  • Design ETL pipelines for new and existing OLAP Data Cubes
  • Design data schema, perform data transformations and manipulations with efficiency and reusability in mind
  • Planning, conducting and directing the analysis of complex business problems

Skills/Experience

  • Understand data structures and algorithms. Understanding of basic statistics (confidence intervals, statistical significance, etc)
  • Experience in working with large size data sets (Billions of rows/Petabytes of data)
  • Experience with building and maintaining ETL pipelines, Data Warehousing and Dimensional Modeling with relational and MPP/distributed systems.
  • Experience in working with various data sources (ODBC, flat files, etc)
  • Experience with Spark performance optimization and troubleshooting
  • Experience with event-driven architectures and message processing with message brokers such as Kafka.
  • Implemented Redshift, Snowflake, Azure Data Warehouse, ADLS, S3, Kafka, Presto, EMR, Databricks, or Data Lake Architecture in one or more public clouds.
  • Productionalizing Data Science models at scale.
  • Created Solutions using GCP, Azure, AWS, or other cloud platforms.  Docker and Kubernetes a plus.
  • Developed Big Data/Hadoop applications using Spark, Hive, HBase, Presto or Map Reduce.
  • Experience using CI/CD methodologies within the data space.
  • Understands tools like Terraform and how to implement infrastructure as code.
  • Experience with Tableau and or other Self Service Analytical tools.
  • Experience with Web Analytics (Adobe Analytics/Omniture, Google Analytics, Heap Analytics) 

For consideration Contact Us

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Bristol and Bates worked with the organization on many fronts in helping us scale. It is refreshing having a partner that understands our culture and values.

Seedbox Technologies
Charles Rousseaux, Co-founder, Vice President

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