Offer summary

Qualifications:

Extensive experience with Azure data platforms like Databricks and Azure SQL., Strong leadership skills with a history of full lifecycle data solutions implementation., Proficiency in data engineering, architecture, and Agile methodologies., Excellent communication skills and ability to interact with technical and non-technical stakeholders..

Key responsibilities:

Design and implement data movement and analytics solutions in Azure.

Lead and contribute to all phases of Agile solution delivery, including analysis, design, development, and testing.

Collaborate with stakeholders to identify gaps and develop comprehensive data strategies.

Manage and deploy Azure services independently, ensuring scalable and efficient data architectures.

Job description

Senior Azure Data Architect/Engineer

Someone who possesses:

Excellent written and verbal communication skills, and presentation skills
Aptitude at both seeing the "big-picture" and acting hands-on at a deep technical level
An ability to easily interact and drive meetings with technical and functional stakeholders
Leadership experience with multiple Full Lifecycle Implementations of Data Movement and Analytics Solutions
Extensive experience within Azure Environments and able to act independently to stand up services as part of a solution
Abilities to identify gaps in an overall program/project across all solution delivery capabilities
Seasoned skills to contribute and if necessary lead all phases of an Agile solution delivery life cycle, from business analysis, design, development, test and DevOps.
Extensive familiarity with both batch (slow) and streaming (fast) data movement approaches in mission critical settings
Problem solving where out-of-the-box thinking is required

Experience with:

Data Engineering and Architecture in an Agile work environment
Extensive knowledge of Azure data platforms such as Databricks, Azure SQL, etc.
Master Data Management principles and processes
Automation Engineering
Python, PySpark, YAML
Data Mapping and transformations
Data Streaming technologies and methodologies
Azure Dev Ops