Data Enablement Consultant

Overview

Remote
Hybrid
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

Amazon Redshift
Amazon SageMaker
Amazon Web Services
Analytical Skill
Apache Spark
Business Intelligence
Continuous Delivery
Continuous Integration
Data Engineering
DMS
Extract
Transform
Load
Geographic Information System
Git
Microsoft Power BI
Migration
Process Optimization
PySpark
Python
SAS
Step-Functions
Tableau
Training
UI
User Experience
Version Control

Job Details

Note: Data Engineer with AWS migration experience

Required Experience:
Consulting with business units to properly define business problem and identify pattern/solution that will resolve the issue.
Consulting with data engineering to ensure solutions are within 'rules' (follow approved patterns) and develop new patterns when necessary.
Experience training BIA, Data Analysts and Data Scientists.
Required Skills:
Experience working with Amazon Web Services (AWS) infrastructure and technologies; DMS, Glue, Step Functions
Ability to train AWS tech Quicksite, Redshift, Sagemaker, Glue
AWS Glue/Spark (PySpark + Spark 3.52)
Python 3.11
QuickSight and Analytic UI/UX
AWS Step Functions & AWS CDK
SageMaker + SageMaker Pipelines
DataOps approaches
Version Control + CI/CD Toolsets (Git, AWS CodeBuild, AWS Code Pipeline)
Ability to train on building access layer in AWS
Ability to provide information about of FCC data pipeline
Ability to map FCC tech debt (SAS, PowerBI, Tableau, etc) to AWS Solutions
Ability to train on FCC Data Observability Framework (DataHub)
Ability to train on GIS
Technical Writing Description of Duties:
Consultants will work with business units comprised of Data Analysts, Business Intelligence Analysts and Data Scientist to execute an adoption plan to migrate existing data assets and process into AWS,
including applying the FCC Data Observability Framework.
The consultants will provide the ongoing support post migration and for the business units developing of new solutions.
The support will include identifying the needs of each business unit and training on the approved patterns needed to fully enable them.
It will also include identifying gaps in the approved patterns and then working with Data Engineering to close those gaps with new patterns, or a process optimization unit if needed.

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