Technical Delivery Lead

EXL Talent Acquisition Team; Pune District; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

EXL Talent Acquisition Team seeks a highly experienced Technical Lead for data engineering and cloud platforms. You will lead teams across Databricks, Snowflake, and lakehouse architectures while guiding governance and data quality initiatives.

You will mentor engineers, drive delivery excellence, and engage clients to align solutions with business priorities, ensuring robust, scalable data ecosystems.

Qualifications

• 12+ years of overall experience in Data Engineering, Data Platforms, Cloud Technologies, AI-enabled data solutions, and enterprise architecture.
• 4+ years in a Technical Leadership role, including team management and delivery ownership.
• Experience leading data engineering initiatives across data platforms and cloud environments.

Responsibilities

• Provide technical leadership across Data Engineering, Cloud, AI, and enterprise data platform initiatives.
• Lead, manage, mentor, and guide engineering teams to ensure high-quality delivery and capability development.
• Drive client engagement by understanding business priorities and communicating technical solutions clearly.
• Collaborate with cross-functional teams including stakeholders, architects, product owners, governance, and delivery leadership.
• Design and review scalable, secure, and cost-effective data architectures, lakehouse platforms, and cloud-based data solutions.
• Support data cataloging, metadata management, data governance, and data quality across platforms.
• Evaluate and implement AI/ML-enabled features and automation to improve platform efficiency.
• Drive best practices in Data Engineering, Cloud, DevOps, CI/CD, performance optimization, and engineering excellence.

Skills

Databricks

Snowflake

Cloud platforms

PySpark

Python

SQL

Data modeling

Data governance

Data cataloging

ETL/ELT pipelines

Data lakes/warehouses

Lakehouse architectures

Automation

AI/ML concepts

Leadership

Client engagement

Tools

Airflow

CI/CD

Git

Terraform

Kubernetes

Job description

Experience

12+ years of overall experience in Data Engineering, Data Platforms, Cloud Technologies, AI-enabled data solutions, and enterprise architecture.

4+ years of experience in a Technical Leadership role, including team management, mentoring, delivery ownership, and stakeholder collaboration.

Role Summary

We are looking for a highly experienced Technical Lead with strong expertise in Data Engineering, AI-enabled data solutions, cloud platforms, data modeling, and data cataloging. The role requires strong technical leadership, team management, and client engagement skills to support enterprise data transformation initiatives. The individual will work closely with clients, leadership, architects, and cross-functional teams to drive solution design, delivery excellence, technology governance, and engineering best practices.

Key Responsibilities

Provide technical leadership across Data Engineering, Cloud, AI, and enterprise data platform initiatives.

Lead, manage, mentor, and guide engineering teams to ensure high-quality delivery and continuous capability development.

Drive effective client engagement by understanding business priorities, managing expectations, communicating technical solutions clearly, and ensuring timely resolution of concerns.

Collaborate with cross-functional teams including business stakeholders, architects, product owners, engineering teams, governance teams, and delivery leadership.

Design and review scalable, secure, and cost-effective data architectures, data models, lakehouse platforms, and cloud-based data solutions.

Support data cataloging, metadata management, data governance, data quality, and compliance practices across enterprise data platforms.

Evaluate and implement AI/ML-enabled features, automation opportunities, and intelligent data engineering practices to improve platform efficiency and business outcomes.

Drive best practices in Data Engineering, Cloud, Data Architecture, DevOps, CI/CD, performance optimization, and engineering excellence.

Participate in technical assessments, solution reviews, interviews, and capability-building initiatives for Data Engineering roles.

Required Skills

Strong hands-on expertise in Databricks and Snowflake.

Strong experience with AWS, Azure, or GCP cloud platforms.

Strong knowledge of Spark, PySpark, Python, SQL, and large-scale data processing frameworks.

Experience in data modeling, data cataloging, metadata management, data governance, and enterprise data management practices.

Experience building Data Lakes, Data Warehouses, Lakehouse platforms, ETL/ELT pipelines, and orchestration workflows.

Understanding of AI/ML concepts, GenAI-enabled data solutions, automation use cases, and AI-driven engineering practices.

Strong team management, stakeholder management, client engagement, communication, and problem-solving skills.

Preferred Skills

Experience in Banking and Capital Markets, or Financial Services domain.

Exposure to data security, regulatory compliance, risk controls, and enterprise governance frameworks.

Experience supporting hiring, technical evaluations, competency development, and engineering capability improvement initiatives.

Key Attributes

Strong technical depth across modern data, cloud, AI, and enterprise architecture ecosystems.

Proven leadership experience in managing teams, driving delivery excellence, and building high-performing engineering capabilities.

Excellent client-facing communication skills with the ability to manage expectations professionally and build trusted relationships.

Ability to work effectively with cross-functional teams and influence stakeholders across technical and business groups.

Strategic thinker with a hands-on technical mindset and strong ownership of outcomes.