COE Lead - Data Engineering (Databricks & Azure)

About Exponentia.ai

Exponentia.ai

is a fast-growing AI-first technology services company, partnering with enterprises to shape and accelerate their journey to AI maturity. With a presence across the

US, UK, UAE, India, and Singapore

, we bring together deep domain knowledge, cloud-scale engineering, and cutting-edge artificial intelligence to help our clients transform into agile, insight-driven organizations. We are proud partners with global technology leaders such as

Databricks, Microsoft, AWS, and Qlik

, and have been consistently recognized for innovation, delivery excellence, and trusted advisories.

Awards & Recognitions: Innovation Partner of the Year – Databricks, 2024 Digital Impact Award, UK – 2024 (TMT Sector) Rising Star – APJ Databricks Partner Awards 2023 Qlik’s Most Enabled Partner – APAC

With a team of

450+ AI engineers, data scientists, and consultants

, we are on a mission to redefine how work is done, by combining human intelligence with AI agents to deliver exponential outcomes.

Learn more:

About the Role: We are looking for a

CoE

Lead – Data Engineering (Databricks & Azure)

to drive and scale our modern data engineering practice across the organization. This leadership role will be responsible for defining the technical vision, establishing best-in-class engineering standards, and overseeing the successful delivery of enterprise-grade data and AI platforms built on

Databricks and Microsoft Azure

.

As the CoE Lead, you will combine

deep hands-on expertise in Data and AI

with strategic oversight, ensuring architecture consistency, platform convergence, and engineering excellence across engagements. You will act as the primary technical authority for data engineering initiatives, guiding solution design, mentoring senior engineers and architects, and partnering with business and client stakeholders to deliver measurable outcomes.

The ideal candidate brings

strong practical experience delivering Data and AI solutions using Databricks and Azure

, along with prior exposure to

Tier 1 or Tier 2 organizations

, reflecting the scale, governance maturity, and complexity expected from this role.

Key Responsibilities: CoE Leadership & Strategy: Define and own the

Data Engineering CoE vision, roadmap, and operating model

across Databricks and Azure. Establish

architecture standards, reference patterns, best practices, and governance

for modern data platforms. Drive alignment across platforms (Databricks, Azure Data Services, Fabric where applicable) to avoid silos. Partner with leadership on

capability building, investments, and GTM strategy

for data engineering offerings. Architecture & Technical Excellence: Act as the

final technical authority

for solution design and architecture reviews. Design and oversee

end-to-end data architectures

including ingestion, transformation, storage, and consumption. Guide teams on: Lakehouse architecture (Delta Lake) Batch and streaming pipelines Data modelling and performance optimization Security, governance, and cost optimization Ensure solutions are scalable, reliable, and aligned with enterprise standards. Delivery & Execution Oversight: Provide technical and delivery oversight across multiple engagements. Support complex problem-solving and unblock teams during critical phases. Ensure adherence to Agile delivery practices, SLAs, and quality benchmarks. Collaborate closely with program managers and architects to ensure predictable delivery. Stakeholder & Client Engagement: Act as a

trusted advisor

to senior client stakeholders (CXOs, Data Heads, Architects). Lead technical discussions, solution walkthroughs, and proposal responses. Support pre-sales activities including

solutioning, estimations, and technical presentations

. Build long-term client relationships through credibility and execution excellence. Team Building & Mentorship: Build, mentor, and scale high-performing data engineering teams. Define

skill frameworks, learning paths, and certification plans

for the CoE. Coach senior engineers and architects on both technical depth and leadership skills. Drive a strong engineering culture focused on quality, ownership, and continuous improvement.

Ideal Candidate Profile 10 - 12 years

of overall experience with strong depth in Data Engineering and Data Platforms. Proven experience leading a Data Engineering, Data or AI CoE, practice, or large delivery teams. Current or prior experience in Tier 1 or Tier 2 organizations is strongly preferred

. Deep hands-on expertise with: Databricks (Spark, Delta Lake, Unity Catalog, Jobs, Workflows) Azure Data Platform (ADLS, ADF, Synapse, Azure SQL, Event Hubs, etc.) Strong experience with

modern data architecture patterns

(Lakehouse, Lambda/Kappa). Solid understanding of

data governance, security, and cost management

on Azure. Demonstrated ability to balance

hands-on problem solving with strategic leadership

. Strong communication skills with the ability to engage senior technical and business stakeholders. Experience working in

consulting or client-facing environments

is highly preferred.