Job Description

We are seeking a highly experienced Solutions Architect specializing in Data Engineering and Analytics to design, build, and deploy scalable cloud-based data platforms. The ideal candidate will have deep expertise in Azure and Databricks, strong architectural knowledge of Data Lakehouse solutions, and a proven ability to guide teams in implementing enterprise-grade data platforms.
Key Responsibilities
Architect & Design: Lead the design and implementation of Data Lakehouse architectures, including batch and real-time streaming pipelines using Delta Lake.
Cloud Data Platforms: Build and optimize scalable data engineering solutions leveraging Azure Data Factory, Databricks, ADLS, Azure Event Hub, PySpark/Scala/SQL.
Data Governance & Cataloging: Drive the adoption and implementation of Unity Catalog, ensuring robust data lineage, governance, schema, and access control mechanisms.
Performance & Cost Optimization: Review solutions and guide teams on performance tuning, cloud cost optimization, and architectural best practices.
Technical Leadership: Act as a trusted advisor to engineering teams, providing hands-on guidance in data engineering, analytics, and cloud-native design patterns.
Innovation & Strategy: Evaluate new tools, frameworks, and approaches to continuously improve the enterprise data ecosystem.
Key Skills & Experience
12+ years in Data Engineering & Analytics with strong focus on cloud-based platforms.
Proven expertise in Azure Cloud Services, Databricks, Delta Lake, and Lakehouse architectures.
Hands-on experience with PySpark, Scala, and SQL for building large-scale data pipelines.
Strong knowledge of data governance, security frameworks, and data cataloging tools (Unity Catalog preferred).
Experience with streaming technologies (Azure Event Hub, Kafka, or similar).
Strong understanding of data pipeline frameworks, distributed computing, and performance optimization.
Excellent communication, leadership, and stakeholder management skills.

Skills Required