Data Architect

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: www.exponentia.ai

About The Role

We are looking for a highly skilled

Data Architect

with hands-on experience in modern cloud-based data platforms and strong working knowledge of Databricks. The candidate will architect scalable data ecosystems, design end-to-end data pipelines, and establish data standards to support advanced analytics, BI, and AI initiatives.

Key Responsibilities

Data Architecture & Platform Design

• Design and implement scalable enterprise data architectures across cloud environments.
• Develop conceptual, logical, and physical data models for analytical and operational use cases.
• Define data ingestion, transformation, and integration patterns using Databricks, Delta Lake, and related frameworks.
• Architect ELT/ETL pipelines leveraging Databricks Workflows, Delta Live Tables, or orchestration tools.
  

Databricks & Lakehouse Responsibilities

• Develop and optimize data pipelines on Databricks (SQL, Python, PySpark).
• Implement Lakehouse architecture principles using Delta Lake, Unity Catalog, and Databricks compute clusters.
• Optimize Spark jobs, cluster configurations, and cost/performance strategies.
• Work with Databricks features such as feature store, MLflow, Delta Sharing, and workspace governance.
  

Data Governance & Quality

• Define data quality rules, lineage, metadata standards, and governance frameworks.
• Collaborate with security teams to ensure compliance with data privacy and security requirements.
• Implement governance structures using Unity Catalog, RBAC, and data access policies.
  

Cross-functional Collaboration

• Partner with data engineers, analysts, AI/ML teams, and business stakeholders to deliver data-driven solutions.
• Translate business needs into scalable, secure, and efficient data architectures.
• Provide architectural guidance and best practices around Databricks and cloud data systems.
  

Strategy & Innovation

• Evaluate data technologies and recommend tooling aligned with modernization and scalability goals.
• Drive cloud migration and transformation initiatives, including legacy system modernization.
• Contribute to the long-term enterprise data architecture roadmap.