Data Engineering Manager

Senior Manager, Database Engineering

Location: Hyderabad, India

Overview

We are seeking a highly strategic and execution-focused Senior Manager of Database Engineering to lead our Hyderabad Data Engineering teams in the design, modernization, and scaling of our enterprise data platforms. This leader will drive innovation across OLTP, Data warehousing, and AI/ML workloads while building and mentoring a high-performing engineering team.

This role combines deep technical expertise with operational excellence. The ideal candidate has successfully scaled cloud data platforms, built strong engineering cultures, and delivered resilient, secure, and high-performance database systems in fast-growing environments.

 

Key Responsibilities

Strategic Leadership & Execution

• Define and execute the long-term data platform strategy aligned with business growth and scalability objectives.
• Lead cloud-first database architecture initiatives leveraging Microsoft Azure services.
• Drive modernization of legacy systems to scalable, high-availability cloud architectures.
• Ensure on-time, high-quality execution of data engineering roadmaps.
• Establish KPIs, SLAs, and operational metrics to ensure reliability and performance.

Cloud & Data Platform Architecture

• Oversee architecture, optimization, and governance of:
• Scaled out architecture of more than 5k Databases
• Azure SQL Server
• Azure Data Factory
• Azure Data Lake
• Azure Databricks
•  
• Design scalable, secure, and cost-efficient database and analytics platforms.
• Implement performance tuning, indexing strategies, partitioning, and high-availability solutions.
• Ensure robust disaster recovery, backup strategies, and compliance controls.

AI & Advanced Analytics Enablement

• Partner with AI/ML teams to build scalable data pipelines supporting advanced analytics and AI initiatives.
• Enable real-time and batch data processing using Databricks and Spark.
• Architect data platforms optimized for machine learning workloads.
• Promote data quality, observability, and governance to support AI-driven decision-making.

Team Building & Organizational Development

• Recruit, mentor, and retain top database and data engineering talent.
• Build a culture of accountability, ownership, and operational excellence.
• Develop career growth frameworks and technical leadership within the team.
• Foster collaboration across engineering, product, security, and analytics teams.
• Lead through influence while promoting continuous learning and innovation.

Scalability & Operational Excellence

• Design systems capable of handling rapid growth in data volume and transaction scale.
• Implement automation, CI/CD, infrastructure-as-code, and DevOps best practices.
• Drive cost optimization initiatives across Azure environments.
• Establish proactive monitoring, alerting, and performance management processes.
• Lead incident response and root-cause analysis efforts.

 

Qualifications

Required

• 10+ years of experience in database engineering, data platform architecture, or related roles.
• 5+ years of engineering leadership experience managing high-performing technical teams.
• Deep expertise in:
• Microsoft Azure cloud services
• SQL Server / Azure SQL
• Azure Databricks & Spark
• Snowflake / Data warehousing and distributed data systems
• Experience supporting AI/ML data workloads.
• Proven track record scaling enterprise-grade data platforms.
• Strong experience in performance tuning, high availability, and security best practices.
• Experience driving execution in agile, fast-paced environments.

Preferred

• Experience with large-scale SaaS or enterprise transactional systems.
• Familiarity with data governance and regulatory compliance frameworks.
• Experience with containerization and Kubernetes in Azure.
• Certifications in Azure (e.g., Azure Solutions Architect, Data Engineer).

 

Leadership Competencies

• Execution-oriented and results-driven.
• Strategic thinker with strong technical depth.
• Builder of high-performance teams.
• Exceptional cross-functional communicator.
• Data-driven decision maker.
• Change agent who thrives in transformation initiatives.

 

What Success Looks Like

• Modernized and scalable Azure-based data architecture.
• High-performing and engaged database engineering team.
• Improved performance, reliability, and cost efficiency.
• AI-ready data platform supporting innovation and analytics.
• Strong governance and operational discipline.