Job Responsibilities
Data Architecture and Strategy:
Develop and oversee the data architecture roadmap, producing target-state designs that align with organizational objectives and industry standards.
Lead the creation of logical and physical data models, ensuring scalability, reliability, and performance across Silver and Gold data layers.
Establish guidelines for ETL/ELT processes, data governance, and lineage to guarantee consistent and high-quality data delivery.
Perform technical assessments and health checks on data initiatives to confirm compliance with architectural principles.

DataOps and Platform Design (Bridge Function):
Act as the intermediary with Infrastructure, translating data requirements such as compute, storage, and security into detailed technical specifications for implementation through Terraform or Infrastructure-as-Code.
Review Infrastructure-as-Code deliverables (Terraform, Ansible) to ensure they meet the demands of data workloads.
Design and oversee CI/CD pipelines for data applications using Azure DevOps, ensuring automated testing, version control, and seamless deployment.
Formulate containerization strategies for data applications using Docker and Kubernetes, defining scalability and networking requirements for Infrastructure teams to deliver.

Reliability and Observability Design:
Set observability standards including logging, metrics, and alerting policies for data platforms, ensuring monitoring integration through tools such as Azure Monitor or Grafana.
Lead the development of resilient “self-healing” architectures, defining recovery point and recovery time objectives for Infrastructure support.
Work closely with Infrastructure teams during major incidents, providing architectural guidance and conducting root cause analysis from a data perspective.

Leadership and Governance:
Champion the adoption of DataOps practices, driving automation in testing, deployment, and data quality assurance.
Assess new technologies including AI/ML solutions and emerging Azure capabilities, proposing proof-of-concept projects to maintain a modern platform.
Provide mentorship to Data Engineers on cloud architecture, compliance, and performance optimization best practices.

Job Requirements

Education and Experience:
Bachelor’s degree in Computer Science, Information Technology, or related disciplines.
At least seven years of IT experience, combining expertise in Data Engineering and Cloud or Solution Architecture.
Demonstrated experience serving as a technical lead or liaison between development and infrastructure/platform teams.

Technical Skills:
Extensive knowledge of Azure data services including Databricks, Data Factory, Synapse, and Data Lake Gen2, with a strong understanding of their interaction with infrastructure components such as networking and private endpoints.
Proficiency in data architecture concepts including data modeling, SQL optimization, and modern frameworks such as Lakehouse, Mesh, and Medallion Architecture.
Ability to interpret and review Infrastructure-as-Code written in Terraform or Ansible, enabling effective communication with SRE teams.
Strong grasp of DevOps principles, including CI/CD pipelines (Azure DevOps, Jenkins), container orchestration (Kubernetes), and version control methodologies such as GitFlow.

Soft Skills and Competencies:
Exceptional communication skills with the ability to bridge the gap between data requirements and infrastructure specifications.
Strategic mindset with the capability to design solutions for long-term scalability and resilience.
Proven leadership experience in mentoring technical teams and influencing stakeholders without direct authority.
Fluency in written and spoken English, with experience in multicultural work environments considered advantageous.

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