What are the responsibilities and job description for the Azure Data Engineer position at Agility Partners?
Agility Partners is looking for a Senior Data Engineer to build data pipelines, model and prepare data, perform complex data analysis to answer Business questions, build and automate data pipeline and quality framework to enable and promote self service data pipelines, assist in operationalizing the AI / ML Engineering solutions. This role is expected to lead and guide other team members and evangelize the design patterns as well as coding standards.
Scroll down to find an indepth overview of this job, and what is expected of candidates Make an application by clicking on the Apply button.
This role plays an active part in our client's Data Modernization project to migrate from on-prem platforms such as IBM Netezza to cloud.
In this role, you will :
- Team up with the engineering teams and enterprise architecture (EA) to define standards, design patterns, accelerators, development practices, DevOps and CI / CD automation.
- Create and maintain the data ingestion, quality testing and audit framework.
- Conduct complex data analysis to answer the queries from Business Users or Technology team partners either directly from Analysts or stemmed from one of the Reporting tools such as PowerBI, Tableau, OBIEE.
- Build and automate the data ingestion, transformation and aggregation pipelines using Azure Data Factory, Databricks / Spark, Snowflake, Kafka as well as Enterprise Scheduler tools such as CA Workload automation or Control M.
- Setup and evangelize the metadata driven approach to data pipelines to promote self service.
- Setup and continuously improve the data quality and audit monitoring as well as alerting.
- Constantly evaluate the process automation options and collaborate with engineering as well as architecture to review the proposed design.
- Demonstrate mastery of build and release engineering principles and methodologies including source control, branch management, build and smoke testing, archiving and retention practices.
- Adhere to and enhance and document the design principles, best practices by collaborating with Solution and in some cases Enterprise Architects.
- Participate in and support the Data Academy and Data Literacy program to train the Business Users and Technology teams on Data.
- Respond to SLA driven production data quality or pipeline issues.
- Work in a fast-paced Agile / Scrum environment.
- Identify and assist with implementation of DevOps practices in support of fully automated deployments.
- Document the Data Flow Diagrams, Data Models, Technical Data Mapping and Production Support Information for Data Pipelines.
- Follow the Industry standard data security practices and evangelize the same across the team.
Benefits and Perks
The Ideal Candidate
J-18808-Ljbffr
