Data Engineer (AVP)
Roles & Responsibilities : Tracking and Reporting processes covering KPIs, including deliverables and project/program updates, budget, and risks/mitigations for use by the CEO and other governance bodies.
*Playing a key role in implementing the Agile process, tools, and protocols, including documentation processes, as well as product standards within the GIC for all project and program work within their remit, using modern tools, team structures, and technology.
*Taking responsibility as required for interfacing with 3rd Party service providers within the Data Engineering department scope, including external 3rd party data and technology services.
*Taking responsibility as required for the project management, Devops, Quality management, and release management functions for all products and platforms built and released by the center, in the specific areas within the scope of the Data Engineering department Understanding of process for Algo and Model Prototyping, Construction, and Validation using Agile approach
Understanding of Supervised and Unsupervised ML paradigms
Exposure to Core Frameworks (Tensorflow, Caffe, PyTorch, SparkMLlib, etc.)
Exposure AI ML Platform Services including AutoML (AWS Sagemaker, AutoPilot)
Cloud Services: AWS (Sagemaker, Lake Formation, S3, EC2, etc.), Google Cloud, Azure Services, AWS Services – S3, AWS SageMaker
Databases: MySQL, MS SQL, Oracle, Neo4J
Data Automation: Lake Formation, Palantir Foundry, Spark
Data Analytics Tools: Power BI, Palantir Foundry, HubSpot, Google Analytics
Tools and Environments: JIRA, Bitbucket, Confluence, Palantir Foundry, Jupyter Notebook, MLFlow