Enterprise Data Architect

Adani; Ahmedabad District; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Adani in Ahmedabad seeks a Senior Enterprise Data Platform Architect to design and govern a scalable cloud-native data platform on Microsoft Azure using Databricks and Delta Lake. You will lead data engineering, ML and analytics initiatives, define standards, ensure data quality, security and cost efficiency, and collaborate with business stakeholders.

The role requires 15–20 years IT experience, 5+ in senior architecture, TOGAF preferred, and strong Azure/Databricks credentials; aviation or

Qualifications

• 15–20 years in IT with at least 5+ years in a senior architectural capacity.
• Experience leading data engineering and analytics programs on Azure and Databricks.
• Familiarity with aviation or large infrastructure domains is preferred.
• TOGAF or equivalent enterprise architecture certification is highly preferred.

Responsibilities

• Architect and design a scalable enterprise data platform on Azure using Databricks and Delta Lake.
• Lead data engineering, analytics, and ML initiatives end-to-end.
• Define and govern cloud architecture standards, security, and cost optimization.
• Mentor platform and data engineering teams and drive technical consensus.
• Collaborate with stakeholders to translate aviation operations into scalable data solutions.

Skills

Databricks

Azure Cloud

Data Architecture

Big Data

MLOps

Education

Bachelor's/Master's in CS/IT

TOGAF certification

Tools

Azure Data Factory

Kafka

PostgreSQL

MongoDB

Spark

Delta Lake

Power BI

Azure IoT Hub

Docker

Kubernetes

MLflow

Airflow

Job description

• Analyze the business requirements and needs of the organization.
• Architect and design robust, scalable, and secure enterprise data platform leveraging Databricks and various cloud services on Microsoft Azure.
• Lead implementation of advanced data analytics solutions utilizing Databricks and Delta Lake architectures to extract, transform, and load (ETL) data.
• Leverage Databricks to perform data engineering, artificial intelligence and machine learning tasks.
• Collect, process, and analyze large datasets from various sources within the aviation domain (e.g., flight data, baggage information, weather data, operational logs etc.).
• Perform data quality checks and ensure data accuracy and consistency.
• Identify trends, patterns, and anomalies in data to provide valuable insights and support business decision-making.
• Contribute to the development of data models and database designs.
• Document data sources, data flows, and analytical processes.
• Stay up to date with the latest trends and technologies in data analysis and the aviation industry.
• Create insightful and interactive data visualizations and reports using tools like Power BI to communicate findings to non-technical audiences.
• Define and govern enterprise-wide cloud architecture standards, security protocols, and operational best practices.
• Developing and implementing strategies to connect different systems, ensuring they can share data and functionality
• Defining and managing API that allow different software applications to communicate with each other
• Defining and managing asynchronous data exchange between applications and as a part of data pipelines
• Diving deep into the details to solve complex technical challenges
• Ensure the platform is secure and adheres to best practices for data protection and privacy.
• Ensuring high data quality and integrity to avoid operational failures and improve system accuracy
• Perform regular audits and maintenance of the platform to ensure its continued performance and stability.
• Support project management activities, resource monitoring, technical risk identification & mitigations
• Mentor and provide technical leadership to platform engineering and data engineering teams.
• Ensure continuous platform optimization, cost management, and high availability of critical analytics infrastructure.
• Partner with business stakeholders to translate airport operational requirements into technical blueprints and scalable solutions.

Qualifications

Required Qualifications & Experience

• Microsoft Certified: Azure Solutions Architect Expert or equivalent advanced architectural certification.
• Databricks Certified Data Engineer Professional or similar advanced credential in big data ecosystems.
• Proven track record of designing large-scale digital platforms in complex operational environments, preferably within aviation or large infrastructure.

Educational Background

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related technical discipline.
• Advanced certifications in Enterprise Architecture frameworks such as TOGAF are highly preferred.

Years & Type of Experience

• 15 to 20 years of progressive experience in IT, with at least 5+ years in a senior architectural capacity.
• Demonstrated experience leading large-scale data engineering and analytics transformation programs utilizing Microsoft Azure and Databricks.

Domain Expertise

• Deep functional knowledge of cloud computing paradigms (IaaS, PaaS, SaaS) and distributed data systems.
• Strong understanding of big data ecosystems, data warehousing, and modern data mesh architectures.
• Familiarity with the aviation or large-scale infrastructure domain, including passenger processing, non-aero revenue analytics, and airport operations.

Digital & Operational Tools

• Data & Analytics: Expertise in Databricks, Apache Spark, Delta Lake, and enterprise Business Intelligence platforms.
• Expertise in databases like PostgreSQL, MS SQL, and MongoDB.
• Expertise in APIs, ESB (Enterprise Service Bus), and Kafka.
• Integration with IoT platforms (Azure IoT Hub), device protocols (MQTT, AMQP, HTTP)
• Experience of data analytics, business intelligence, and AI/ML technologies
• Use of AI tools for code generation, pipeline automation, testing
• Knowledge of Azure DevOps, Docker, Kubernetes, and enterprise source control systems.
• Understanding of machine learning fundamentals (supervised, unsupervised, feature engineering)
• Experience supporting ML model lifecycle (training data, inference pipelines)
• Exposure to LLMs, GenAI pipelines, and vector databases
• Knowledge of feature engineering and model-ready datasets
• Knowledge of MLOps tools (MLflow, Kubeflow, Airflow, etc.)
• Building CI/CD pipelines for data + ML workflows
• Experience of Agile methodologies, Jira, and Confluence.
• Knowledge of cybersecurity principles and practices.

Leadership Capabilities

• Ability to drive technical consensus and influence technology strategy across diverse stakeholder groups and executive leadership.
• Strategic thinker with a demonstrated capability to align IT and platform roadmaps with long-term business objectives.
• Proven track record of mentoring senior engineers and fostering a culture of technical excellence and innovation.
• Capable of managing complex, multi-million dollar technology initiatives and strategic vendor relationships.

Job Info

• Job Identification 53636
• Job Category Information Technology
• Posting Date 06/25/2026, 11:31 AM
• Locations Commerce House 6, Ahmedabad, Gujarat, 380051, IN
• Apply Before 09/30/2026, 11:31 AM
• Job Schedule Full time