Data Architect

EXL; Gurugram District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

EXL in India seeks a Data Engineer Senior Manager to drive end-to-end data engineering initiatives and lead cross-functional teams delivering cloud-based data solutions. You will mentor onshore/offshore engineers, shape architecture with Azure services, and ensure scalable data pipelines using PySpark, SQL, Databricks, and CI/CD practices.

The role emphasizes strong leadership, stakeholder collaboration, and hands-on delivery across enterprise-scale projects in a fast-paced environment.

Qualifications

• 12+ years of experience in Data Engineering with proven experience in delivering enterprise-scale projects.
• Strong expertise in Batch Systems, distributed systems, and cloud-native architectures.
• Proficiency in Data Bricks, SQL, and a wide range of Azure services (e.g., Synapse, Dedicated SQL Pool, ADLS, Spark Pool, Azure Data Factory, Power BI).
• Hands-on experience with Python, PySpark, and building cloud-based microservices.

Responsibilities

• Lead and mentor a team of onshore and offshore data engineers to ensure high-quality deliverables.
• 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.
• Oversee end-to-end project delivery with timely, high-quality execution and stakeholder communication.

Skills

Leadership

Data Engineering

Cloud Data

Azure

PySpark

Python

SQL

Agile/Scrum

Communication

Tools

Azure Synapse

ADLS

Spark Pool

Databricks

Azure Data Factory

Power BI

CI/CD

Jenkins

Git

GitHub/GitLab

Job description

Description We are seeking a highly skilled Data Engineer Senior Manager to drive end-to-end data engineering initiatives, lead cross-functional teams, and deliver scalable, cloud-based data solutions. The ideal candidate will bring deep technical expertise, strong leadership, and the ability to collaborate effectively with global stakeholders in a fast-paced environment. Responsibilities Key Responsibilities

Leadership & Team Management

• 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 build capability.
• Establish and enforce engineering best practices, coding standards, and reusable frameworks.

Champion innovation, continuous learning, and thought leadership within the data engineering function.

Project Delivery & Execution

• Oversee end-to-end project delivery, ensuring timely, high-quality execution aligned with project 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.

Stakeholder Communication & Collaboration

• Collaborate with clients, product owners, business leaders, and offshore teams to gather requirements and define technical solutions.
• Communicate project updates, timelines, risks, and technical concepts effectively to both technical and non-technical stakeholders.

12+ years of experience in Data Engineering with proven experience in delivering enterprise-scale projects.

• Strong expertise in Batch Systems, distributed systems, and cloud-native architectures.
• Proficiency in Data Bricks, SQL, and a wide range of Azure services (e.g., Synapse, Dedicated SQL Pool, ADLS, Spark Pool, Azure Data Factory, Power BI).
• Hands-on experience with Python, PySpark, and building cloud-based microservices.
• Strong problem-solving, analytical skills, and end-to-end ownership mindset.
• Proven ability to work in Agile/Scrum environments with iterative delivery cycles.
• Exceptional communication, leadership, and stakeholder management skills.
• Demonstrated capability in leading offshore teams and coordinating multi-region delivery efforts.
• Good exposure with Azure Identity management (SPN, UMI, MI).
• Experience in Data Observability using DataDog/Splunk.
• Experience with DevOps tools (Jenkins, Git, GitHub/GitLab) and CI/CD pipeline implementation.