Principal Data Engineer

Reposted Yesterday
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Pune, Mahārāshtra, IND
In-Office
Expert/Leader
Information Technology • Travel
The Role
Lead and mentor a data engineering team to design, build, and maintain scalable data architecture and ETL pipelines across cloud and on‑prem platforms. Drive cloud migration (Azure), event‑driven solutions (Kafka/Event Hub), operational reliability, AI adoption, and cross‑functional collaboration while managing delivery, incidents, and stakeholder communication.
Summary Generated by Built In

Job Title

Principal Data EngineerRole Overview

The Data Engineering Manager / Team Lead will lead a high-performing data engineering team in a large-scale, fast-paced environment, managing both cloud and on-premise data platforms. This role is responsible for designing, building, and maintaining scalable data architecture, ETL pipelines, and data processing systems aligned with customer needs and business objectives.

This leader will drive technical excellence, operational efficiency, innovation, and AI adoption while managing delivery, people, and cross-functional collaboration.

Core ResponsibilitiesLeadership & Team Management
  • Lead and mentor a data engineering team, ensuring high technical and delivery standards.
  • Manage team capacity, delegation, sprint/user story assignments, and backlog prioritization.
  • Provide technical coaching, code reviews, and guidance to engineers and senior specialists.
  • Drive adoption of AI agents and AI-assisted development/documentation across the team.
  • Deliver regular status updates, including weekly burndown and progress reporting.
Data Engineering & Architecture
  • Design, develop, and maintain scalable data pipelines, ETL workflows, and data architecture.
  • Build programs for data ingestion, transformation, validation, and integration.
  • Support migration of legacy/on-prem data systems to cloud data platforms.
  • Work with structured and unstructured data across multiple formats.
Cloud & Modern Data Platform Engineering
  • Lead modernization initiatives across cloud-native platforms, with emphasis on:Azure CloudDatabricksAirflow / Azure Data Factory / Synapse PipelinesEvent-driven data systems (Kafka / Event Hub)
Operational Excellence
  • Manage production data processes and respond to incidents/issues.
  • Ensure system reliability, performance, and scalability.
  • Monitor infrastructure utilization:CPUMemoryStorageNetwork
  • Improve processes and reduce operational inefficiencies.
Strategic & Cross-Functional Collaboration
  • Translate business requirements into technical solutions.
  • Work effectively across multiple time zones and distributed teams.
  • Collaborate with Product, Development, Operations, and Customer Support teams.
  • Communicate risks, dependencies, blockers, and mitigation plans to leadership.
Technical RequirementsRequired Skills
  • Big Data Engineering / Data Platform Management
  • Python for ETL, orchestration, and automation
  • Advanced SQL development and performance tuning
  • ETL development and orchestration
  • Database development (Oracle, MySQL, PostgreSQL, SQL Server)
  • UNIX / Shell scripting
  • JSON / API-based integrations
  • Master Data Management (MDM)
  • Cloud platforms (Azure preferred)
  • Data migration to cloud platforms
  • Event streaming / messaging systems:KafkaAzure Event HubSimilar queuing systems
Preferred Skills
  • Databricks (Highly Preferred)
  • Apache Airflow
  • Kubernetes
  • Apache Spark
  • Apache Druid
  • Couchbase / NoSQL databases
  • Azure Synapse
  • Stambia
  • Agile delivery methodologies
Key Leadership Expectations

The ideal candidate should demonstrate:

  • Strong technical decision-making capability
  • Ability to solve complex data engineering problems
  • High ownership with minimal supervision
  • Strong stakeholder management and communication skills
  • Ability to balance strategic vision with hands-on technical leadership
  • Confidence to make independent decisions and guide architecture direction
Key Accountabilities
  • Perform database integrity checks and corrective actions
  • Maintain operational procedures and documentation
  • Ensure external vendors/service providers meet SLA commitments
  • Support customer onboarding and product activation
  • Troubleshoot functional and operational issues
  • Coordinate with Product, Help Desk, Operations, and Development teams for escalations
  • Prepare database correction requests and operational checklists
  • Monitor customer satisfaction and address service issues proactively
Ideal Candidate Profile

A successful candidate is a hands-on technical leader with strong experience in modern data engineering, cloud migration, AI-enabled automation, and team leadership, capable of driving both strategic transformation and operational excellence.

Diversity & Inclusion

Amadeus aspires to be a leader in Diversity and Inclusion in the tech industry, enabling every employee to reach their full potential by fostering a culture of belonging and fair treatment, attracting the best talent from all backgrounds, and as a role model for an inclusive employee experience.  

Amadeus is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, race, ethnicity, sexual orientation, age, beliefs, disability or any other characteristics protected by law.  

Be aware of recruitment scams


Amadeus Group never charges fees, requests payment, or asks for financial information during recruitment. All legitimate opportunities are communicated solely through official Amadeus channels, including our careers website. Any payment request or outreach via unofficial platforms (e.g., WhatsApp, Telegram) should be treated as fraudulent.

Skills Required

  • Big Data Engineering / Data Platform Management
  • Python for ETL, orchestration, and automation
  • Advanced SQL development and performance tuning
  • ETL development and orchestration
  • Database development (Oracle, MySQL, PostgreSQL, SQL Server)
  • UNIX / Shell scripting
  • JSON / API-based integrations
  • Master Data Management (MDM)
  • Cloud platforms (Azure preferred)
  • Data migration to cloud platforms
  • Event streaming / messaging systems (Kafka, Azure Event Hub or similar)
  • Team leadership, coaching, and delivery management
  • Databricks
  • Apache Airflow
  • Kubernetes
  • Apache Spark
  • Apache Druid
  • Couchbase / NoSQL databases
  • Azure Synapse
  • Stambia
  • Agile delivery methodologies
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The Company
HQ: Madrid
10,001 Employees
Year Founded: 1987

What We Do

Travel powers progress. Amadeus powers travel. Amadeus’ solutions connect travelers to the journeys they want, linking them via travel agents, search engines and tour operators to airlines, airports, hotels, cars and railways. Technology has always been critical to developing global travel, increasing scale, choice and access. We have developed our technology in partnership with the travel industry for 30 years. We combine a deep understanding of how people travel with the ability to design and deliver the most complex, trusted, and critical systems our customers need.

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