Azure Architect

Role Summary: Lead the design development and optimization of enterprise-scale data platforms and analytics solutions using Azure Databricks. Drive data engineering best practices, mentor team members and collaborate with business stakeholders to deliver scalable, secure and high-performance data solutions. This aligns with OpenKyber's Azure-based Data Analytics ecosystem.

Key Responsibilities:

• Lead the development of scalable data pipelines and ETL/ELT frameworks using Azure Databricks and PySpark.
• Architect and optimize data ingestion, transformation and consumption layers.
• Design data models, data dictionaries and reusable data products.
• Implement data governance, quality, security and compliance standards.
• Optimize Spark workloads, Databricks jobs and overall platform performance.
• Collaborate with business users, data scientists and cross-functional teams to translate requirements into technical solutions.
• Mentor and guide data engineers and junior team members.
• Drive CICD, automation and DevOps best practices for data platforms.
• Support Data Lakehouse architecture and enterprise analytics initiatives.

Required Skills: Azure Databricks, PySpark, Apache Spark, Python, SQL, TSQL, Azure Data Factory, ADF, Azure Data Lake Storage, ADLS, Azure Synapse Analytics, Delta Lake, Databricks Workflows, Data Modeling, Data Warehousing, Azure DevOps, Data Governance, Security, Performance Tuning and Optimization, CICD and Automation Frameworks.

Experience: 10 years in Data Engineering, Data Platform delivery. Strong experience leading Azure-based cloud data transformation programs. Proven expertise in enterprise-scale Databricks implementations. Experience mentoring teams and driving technical governance.

Preferred Skills: Unity Catalog, Airflow, Power BI, Lakehouse Architecture, DataOps/MLOps exposure, Stakeholder management and client-facing communication.

Mandatory Skills: Databricks.

For applications and inquiries,