Zensar is a leading digital solutions and technology services company that specialises in partnering with global organisations across industries in their Digital Transformation journey. Zensar’s Return on Digital® strategy has enabled customers to look beyond current investments towards realising visible business benefits in their digital transformation journey.

If you’re looking for a workplace where associates realise and contribute to their full potential, are recognised for the impact they make, and enjoy the company of the people they work with, then you’ve come to the right place!

We are seeking a highly skilled and versatile Lead SQL DBA to drive the design, implementation, and administration of our enterprise data ecosystem.

This Role is to bridge the gap between Database Administration, Cloud Data Architecture, and Advanced Data Engineering. The ideal candidate will be responsible for managing SQL/Azure environments and leading the engineering design of sophisticated data analytics solutions.

They will take full ownership of data integration, availability, and troubleshooting across business systems including SQL Server, Azure, Power Platform, MS Fabric, Jitterbit, CData, and Salesforce. Additionally, you will implement cutting-edge AI models and modern data architecture frameworks while enforcing robust data governance policies.

Key Responsibilities

Database & Cloud Administration: Administer SQL Server (2019+), Azure SQL, and Azure VMs. Configure and optimise Azure services, including App Registrations, Key Vault, Function Apps, and Logic Apps.
Architecture & Design: Lead the architectural design and development of enterprise-level data platforms. Apply modern frameworks such as Medallion and Lambda patterns. Design high-performance NoSQL (Cosmos DB, MongoDB) and relational schemas (Normalisation, Dimensional Modelling).
Data Engineering: Architect and maintain robust ETL/ELT pipelines using ADF, SSIS, Jitterbit, and MS Fabric. Develop complex data transformations using SQL, Python, and PySpark.

Data Security & Resilience: Define user access rights and enforce data management policies. Set up data protection strategies, including Always On High Availability, Log Shipping, and efficient backup/restore protocols.

Advanced Analytics & AI: Build business logic and presentation layers. Deploy internal GPT models via Azure AI Foundry/Cognitive Services. Manage SQL scripts and Fabric notebooks for automated data validation.

Business Intelligence: Collaborate with executive leadership to deliver interactive Power BI dashboards, curated datasets, and secure semantic models.

Platform Operations: Support data communication and troubleshooting across Salesforce, Oracle EPM, Power Platform, and MS Fabric Lakehouse components (Delta Tables, SQL Endpoints).

Governance & Security: Implement strict Data Governance, including encryption, masking, purging, and Row/Column Level Security (RLS/CLS).

Technical Requirements

Database Management: Expert-level SQL Server, Azure SQL, and NoSQL (Cosmos/Mongo).

Integration Tools: Deep experience with Azure Data Factory, SSIS, Jitterbit, CData, and Logic Apps.

Modern Data Stack: Proficiency in MS Fabric (Dataflows Gen2, Pipelines), Databricks, and ADLS Gen2.

Scripting: Advanced proficiency in SQL, Python, PySpark, and DAX.

Business Applications: Strong familiarity with Salesforce, Power Platform, Oracle EPM, and APIs.

Preferred Certifications

Microsoft: Azure Data Engineer (DP-203, DP-600, or DP-700), Azure Solutions Architect (AZ-305), or Azure Admin (AZ-104).
Data & BI: Databricks Certified Data Engineering Professional or Power BI Data Analyst (PL-300).
Legacy: Microsoft Certified SQL Server DBA.

Experience

Cloud Transformation: Proven experience migrating on-premises SQL environments to Azure (PaaS/IaaS) and architecting scalable cloud-native data lakes.

System Integration: Extensive background synchronising data across disparate enterprise systems (ERP, CRM, EPM) using middleware like Jitterbit or ADF.

Data Delivery: Proven track record of leading full-lifecycle Data Warehouse implementations and operationalising AI/ML workflows (LLMs or predictive models).

Qualification:

Must be educated to at least degree level or equivalent.

Lead Database Administrator

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