We are seeking an experienced Analytics Architect with strong expertise in Azure Databricks and Microsoft Fabric to lead the architecture, design, and delivery of advanced analytics and big data solutions. This role requires deep hands‑on experience in data engineering, cloud‑native analytics platforms, and large‑scale data processing, along with the ability to guide teams and engage closely with business stakeholders.

The ideal candidate will bring strong technical leadership, a solid understanding of end‑to‑end data architectures, and a passion for driving scalable, secure, and high‑performance analytics solutions on Azure.

Key Responsibilities

Lead the architecture, design, and implementation of advanced analytics solutions using Azure Databricks and Microsoft Fabric
Design and deliver solutions on Microsoft Fabric, including Fabric Pipelines, Lakehouse, Warehouse, and Real‑Time Analytics (Eventhouse)
Migrate existing analytics workloads (e.g., Azure Synapse, Databricks, Data Marts) to Microsoft Fabric
Work closely with business stakeholders and IT teams to understand requirements and translate them into effective technical solutions
Own the end‑to‑end delivery of data solutions, ensuring alignment with business needs and industry best practices
Lead development of data pipelines and ETL/ELT processes using Azure Databricks, PySpark, and related tools
Integrate Azure Databricks with other Azure services such as Azure Data Lake, Azure Synapse, Azure Data Factory, and on‑premise systems
Provide technical leadership and mentorship to data engineering teams, promoting continuous learning and improvement
Ensure proper documentation of data architecture, pipelines, processes, and data flows
Enforce best practices around code quality, data security, scalability, and governance
Stay current with the latest capabilities and advancements in Databricks, Microsoft Fabric, and Azure analytics services to drive innovation

Essential Technical Skills

Strong hands‑on experience with Azure Databricks, including cluster management, notebook development, and Delta Lake
Proficiency in big data technologies such as Spark, Hadoop, and processing frameworks like PySpark
Deep understanding of Azure Data Lake, Azure Synapse Analytics, and Azure Data Factory
Experience with ETL/ELT pipelines, data warehousing concepts, and data lake architectures
Advanced SQL skills and familiarity with NoSQL databases
Experience with CI/CD pipelines and version control systems such as Git
Solid knowledge of cloud security best practices

Experience Requirements

8+ years of experience developing data ingestion and transformation pipelines using Databricks / Synapse notebooks and Azure Data Factory
Strong hands‑on experience with Delta Tables, Delta Lake, and Azure Data Lake Storage Gen2
Proven experience using Auto Loader and Delta Live Tables for efficient data ingestion and transformation
Expertise in building and optimizing query layers using Databricks SQL
Demonstrated experience integrating Databricks with Azure Synapse, ADLS Gen2, and Power BI for end‑to‑end analytics solutions
Prior experience developing, optimizing, and deploying Power BI reports and dashboards
Hands‑on exposure to modern CI/CD practices in Databricks and cloud‑native environments

Nice to Have Skills

Power BI for reporting and visualization
Microsoft Fabric for analytics and integration use cases
Spark Streaming for real‑time data processing
Familiarity with Azure Resource Manager (ARM) templates and Infrastructure‑as‑Code (IaC) practices

Soft Skills

Excellent communication skills with the ability to explain complex technical topics to non‑technical stakeholders
Strong analytical and problem‑solving mindset
Proven leadership and mentoring capabilities for managing and guiding data engineering teams
Proactive, detail‑oriented, and collaborative approach to delivery

Education

Bachelor's degree in Computer Science, Engineering, or a related field

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