Role 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 Responsibilities

Leadership & 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 Requirements

Required 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.

Principal Data Engineer