Data Engineering Lead - IT

Experience: 7-12 years in data bricks, data architecture, analytics and enterprise integration roles.

Purpose of the Role The Azure Data & Integration Architect will lead enterprise-wide data and integration initiatives, leveraging Microsoft Azure and Databricks to drive digital transformation, operational efficiency, and data-driven decision-making. This role focuses on architecting scalable data pipelines, designing a unified lakehouse platform, enabling advanced analytics, and integrating enterprise systems across SAP and non-SAP landscapes.

Key Responsibilities 1.Data Architecture & Analytics -

• Implement Unity Catalog for governance, data lineage, and access control.
• Design and deploy enterprise data models and analytical layers using Azure.
• Enable enterprise reporting and self-service analytics through Power BI integration.
• Manage both structured and unstructured data using Azure Blob Storage and Azure Data Lake Storage Gen2.
• Collaborate with data scientists and business teams to enable machine learning and predictive analytics use cases.
• Define and enforce data architecture standards, naming conventions, and performance best practices. 2. Integration & Enterprise Connectivity -
• Design and implement integrations between SAP and non-SAP systems using SAP CPI, Azure API Management, and REST/SOAP APIs.
• Ensure secure and scalable data flow across on-premises, cloud, and hybrid environments.
• Implement API authentication and security protocols (OAuth 2.0, JWT, SAML).
• Integrate enterprise applications with Azure Entra ID for identity and access management.
• Establish reusable integration patterns and frameworks for enterprise-wide adoption. 3.Governance, Security & Compliance -
• Ensure data quality, lineage, and governance across the analytics ecosystem.
• Implement security and compliance controls aligned with GxP, 21 CFR Part 11, and corporate IT policies.
• Monitor cost and performance optimization across Azure services.
• Oversee DevOps and CI/CD pipelines for automated deployment and testing using Azure DevOps. 4.Leadership & Collaboration -
• Collaborate closely with cross-functional IT, data, and business teams.
• Conduct technical design reviews, mentor developers, and ensure adherence to architectural standards.
• Support vendor evaluations, solution assessments, and proof-of-concept initiatives.
• Communicate complex technical concepts effectively to senior management and business stakeholders.

Education & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
• MBA is a plus.

Mandatory Requirements

• Minimum 7+ years of experience in data analytics, engineering, and enterprise integration.
• Proven experience architecting enterprise-scale data platforms on Azure.
• Strong hands-on expertise in Azure Databricks (PySpark, Delta Lake, Unity Catalog).
• Proficiency in Azure Data Factory, Azure Synapse Analytics, Power BI, Blob Storage, and Data Lake Gen2.
• Proficient in integration technologies (SAP CPI, Azure API Management, middleware platforms).
• Deep understanding of data security and identity protocols (OAuth, JWT, SAML) and Azure Entra ID.
• Familiarity with GxP-compliant data handling and governance practices.
• Strong proficiency in Python, PySpark, and SQL, hands on experience in writing clean, efficient and scalable code.
• Exposure to Azure DevOps.

Desirable Requirements

• Experience in pharmaceutical manufacturing and regulatory environments.
• Exposure to Terraform, or ARM templates for infrastructure automation.
• Knowledge of modern data architecture principles (Lakehouse, Data Mesh, ELT).
• Experience with Agentic AI, preferably using Microsoft AI technologies

Preferred Certifications

• Microsoft Certified: Azure Solutions Architect Expert
• Microsoft Certified: Data Engineer Associate
• Microsoft Certified: Identity and Access Administrator Associate