Data Engineering Manager

We are seeking a highly skilled Data Engineering Manager to drive end-to-end data engineering initiatives and lead cross-functional teams. The role focuses on delivering scalable, cloud-based data solutions for global stakeholders. The ideal candidate combines deep technical expertise with strong leadership and stakeholder management skills.

Our client is a leading global technology and analytics company operating in the computer software industry. They serve enterprises across multiple regions with data-driven, cloud-based digital solutions. The organization is known for its fast-paced, collaborative culture and its focus on innovation and continuous learning.

Responsibilities

• Lead and mentor a team of onshore and offshore data engineers to ensure high-quality deliverables.
• Provide technical direction, coaching, and knowledge sharing to foster team growth and capability building.
• Establish and enforce engineering best practices, coding standards, and reusable frameworks.
• Oversee end-to-end project delivery, ensuring timely, high-quality execution aligned with objectives.
• Define high-level solution designs, data architectures, and ETL/ELT frameworks for cloud-based data platforms.
• Drive development, code reviews, unit testing, and deployment to production environments.
• Ensure optimal performance, scalability, and reliability across data pipelines and systems.
• Collaborate with clients, product owners, and business leaders to gather requirements and define technical solutions.
• Communicate project updates, timelines, risks, and technical concepts to both technical and non-technical stakeholders.

Requirements

• 10-12+ years of experience in data engineering with proven delivery of enterprise-scale projects.
• Strong expertise in batch systems, distributed systems, and cloud-native architectures.
• Proficiency in Databricks, SQL, and Azure services (Synapse, Dedicated SQL Pool, ADLS, Spark Pool, Azure Data Factory, Power BI).
• Hands-on experience with Python, PySpark, and building cloud-based microservices.
• Experience working in Agile/Scrum environments with iterative delivery cycles.
• Demonstrated capability in leading offshore teams and coordinating multi-region delivery efforts.
• Good exposure to Azure identity management (SPN, UMI, MI), data observability (DataDog/Splunk), and DevOps tools (Jenkins, Git, GitHub/GitLab) with CI/CD pipeline implementation.
• Bachelor's degree in computer science, software engineering, MIS, or equivalent combination of education and experience.

Skills

Data Engineering, Batch Systems, Distributed Systems, Cloud-native Architectures, Databricks, SQL, Azure (Synapse, Dedicated SQL Pool, ADLS, Spark Pool, Azure Data Factory, Power BI), Python, PySpark, Azure Identity Management (SPN, UMI, MI), Data Observability (DataDog/Splunk), DevOps tools (Jenkins, Git, GitHub/GitLab), CI/CD pipeline implementation, Agile/Scrum