Job Title: Technical Lead – Data Engineering & Data Platforms
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.
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.
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.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
EXL is a leading operations management and analytics company that helps businesses improve their performance.