What are the responsibilities and job description for the Azure Data Architect (Databrick expertise) position at Syrencloud LLC?
About Syren Cloud
Syren Cloud Technologies is a cutting-edge company specializing in supply chain solutions and data engineering. Their intelligent insights, powered by technologies like AI and NLP, empower organizations with real-time visibility and proactive decision-making. From control towers to agile inventory management, Syren unlocks unparalleled success in supply chain management.
Role Summary
An Azure Data Architect is responsible for designing, implementing, and maintaining the data infrastructure within an organization. They collaborate with both business and IT teams to understand stakeholders' needs and unlock the full potential of data. They create conceptual and logical data models, analyze structural requirements, and ensure efficient database solutions.
Job Responsibilities
- Act as subject matter expert providing best-practice guidance on data lake and ETL architecture frameworks suitable for handling big data for unstructured and structured information.
- Drive business and Service Layer development with the customer by finding new opportunities based on expanding existing solutions and creating new ones.
- Provide hands-on subject matter expertise to build and implement Azure-based Big Data solutions.
- Research, evaluate, architect, and deploy new tools, frameworks, and patterns to build sustainable Big Data platforms for our clients.
- Facilitate and / or conduct requirements workshops.
- Responsible for collaborating on the prioritization of technical requirements.
- Collaborates with peer teams and vendors on the solution and delivery.
- Has overall accountability for project delivery.
- Works collaboratively with the Product Management, Data Management, and other Architects to deliver for the cloud data platform and Data as a Service.
- Consults with clients to assess current problem states, define desired future states, define solution architecture, and make solutions recommendations.
- Design and implement scalable and reusable data models to support analytical and operational use cases, ensuring compatibility with various business applications.
- Optimize data models for performance and scalability, addressing key challenges in data latency, volume, and complexity in a big data environment.
- Ensure data quality and consistency by establishing robust data validation and governance mechanisms during the modeling process.
- Collaborate with data scientists, engineers, and business stakeholders to translate business requirements into effective and efficient data models.
Job Requirements