Aditi Consulting
Data Engineer III
Aditi Consulting, Dallas, Texas, United States, 75215
Responsibilities
Plan, design, implement, and manage a deployment of self-service data platform using native AWS servicesDesign, build, and maintain data pipelines using modern Big Data technologies such as AWS Redshift, S3, Glue, Athena, EMR, Spark, Hive, etc.Utilize modern cloud database and storage concepts to for data storage and versioning (Data Lakes with AWS S3)Establish scalable, efficient, automated processes for large scale data analysisBuild data pipelines to feed machine learning models for real-time and large-scale offline use cases.Support the development of performance dashboards that encompass key metrics to be reviewed with senior leadership and sales managementWork with business owners and partners to build data sets that answer their specific business questions
Required Skills & Experience
5+ years of data engineering experienceExperience with data modeling, warehousing and building ETL pipelinesExperience with SQLExperience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJSExperience mentoring team members on best practices
Preferred Skills
Experience with big data technologies such as: Hadoop, Hive, Spark, EMRExperience operating large data warehousesExperience with Native AWS services
Compensation:The pay rate range above is the base hourly pay range that Aditi Consulting reasonably expects to pay someone for this position (compensation may vary outside of this range depending on several factors, including but not limited to, a candidate's qualifications, skills, competencies, experience, location and end client requirements).
Benefits and Ancillaries:Medical, dental, vision, PTO benefits and ancillaries may be available for eligible Aditi Consulting employees and vary based on the plan options selected by the employee.
Aditi Consulting LLC uses AI technology to engage candidates during the sourcing process. AI technology is used to gather data only and does not replace human-based decision making in employment decisions.
Plan, design, implement, and manage a deployment of self-service data platform using native AWS servicesDesign, build, and maintain data pipelines using modern Big Data technologies such as AWS Redshift, S3, Glue, Athena, EMR, Spark, Hive, etc.Utilize modern cloud database and storage concepts to for data storage and versioning (Data Lakes with AWS S3)Establish scalable, efficient, automated processes for large scale data analysisBuild data pipelines to feed machine learning models for real-time and large-scale offline use cases.Support the development of performance dashboards that encompass key metrics to be reviewed with senior leadership and sales managementWork with business owners and partners to build data sets that answer their specific business questions
Required Skills & Experience
5+ years of data engineering experienceExperience with data modeling, warehousing and building ETL pipelinesExperience with SQLExperience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJSExperience mentoring team members on best practices
Preferred Skills
Experience with big data technologies such as: Hadoop, Hive, Spark, EMRExperience operating large data warehousesExperience with Native AWS services
Compensation:The pay rate range above is the base hourly pay range that Aditi Consulting reasonably expects to pay someone for this position (compensation may vary outside of this range depending on several factors, including but not limited to, a candidate's qualifications, skills, competencies, experience, location and end client requirements).
Benefits and Ancillaries:Medical, dental, vision, PTO benefits and ancillaries may be available for eligible Aditi Consulting employees and vary based on the plan options selected by the employee.
Aditi Consulting LLC uses AI technology to engage candidates during the sourcing process. AI technology is used to gather data only and does not replace human-based decision making in employment decisions.