Zimetrics - Lead Azure Data Architect - SQL/Data Warehousing

Overview

Zimetrics is a niche technology services and solutions provider focused on Data, AI and Digital. We enable enterprises to harness the vast economic potential and transformational business value of data from systems, machines, connected devices, and human-generated content.

Founded in 2015, Zimetrics today serves leading global enterprises and innovative start-ups across Healthcare & Life Sciences, Media & AdTech, FinTech & Insurance, Automotive, and Manufacturing.

Role Overview

We are looking for a Data Lead with strong expertise in SQL and data warehousing to drive data understanding, analytics, and reporting across business functions.

The ideal candidate will play a key role in translating complex data into actionable business insights, while ensuring high data quality and scalable architecture.

This role requires a quick learner who can rapidly understand new domains and collaborate effectively with both business and technical stakeholders.

Must-Have Skills

• Strong proficiency in writing, optimizing, and tuning complex SQL queries
• Hands-on experience with Azure Data Factory (ADF) OR Databricks
• Solid understanding of data warehousing concepts, including Medallion Architecture (Bronze, Silver, Gold layers)
• Strong data fundamentals: data models, data lineage, transformations, and data quality checks
• Good understanding of reporting, analytics, and business KPIs
• Ability to quickly learn new domains, business processes, and functionalities
• Excellent analytical, problem-solving, and communication skills
  
  

• Hands-on exposure to Snowflake
• Experience working with ERP systems such as Oracle, SAP, Microsoft Dynamics, or similar platforms
  
  

• Lead data analysis, data modeling, and reporting initiatives
• Partner with business stakeholders to understand requirements and translate them into scalable data solutions
• Collaborate with data engineering teams to design and maintain robust data pipelines and architectures
• Ensure data quality, consistency, governance, and best practices across datasets
• Drive data insights and storytelling to support business decision-making
• Review and optimize SQL queries, data models, and reporting logic
• Guide and mentor data engineers and data analysts, providing technical and analytical direction
  
  

(ref:hirist.tech)