Lead Data Engineer
What You’ll Do
- Lead the design, development, and maintenance of scalable ETL/ELT pipelines and data products in multi-cloud, multi-region, distributed environments.
- Define and apply appropriate data engineering patterns and architectures based on business and technical requirements.
- Drive technical investigations and resolve complex data, operational, and production issues.
- Design scalable, flexible, efficient, and supportable solutions using appropriate technologies and disciplined development practices.
- Provide technical leadership, guidance, and mentorship to data engineering teams.
- Collaborate with architects, engineering teams, and business stakeholders to deliver robust data solutions.
Key Skills
- Data Engineering & Architecture: Strong understanding of data engineering patterns and modern architectures such as Data Mesh, Data Fabric, Data Lake, and Data Warehouse.
- Big Data & Cloud: Proficiency in Amazon EMR, AWS Glue, Data Lake, and technologies for processing large datasets.
- Programming: Strong proficiency in Python, Java, or Scala, with solid OOP expertise.
- Data Warehousing: Strong knowledge of data warehousing solutions, preferably Snowflake.
- ETL/ELT & Orchestration: Hands-on experience with ETL/ELT pipelines and data orchestration tools.
- Databases: Strong expertise in relational and NoSQL databases.
- Data Modelling: Experience designing efficient OLAP and OLTP data models.
- Streaming: Knowledge of streaming data technologies and architectures.
- Version Control: Experience with Git and modern development practices.
- Containers & Orchestration: Understanding of Docker and Kubernetes.
- Data Security: Knowledge of encryption, access control, data privacy, and compliance.
- Monitoring & Logging: Experience implementing monitoring, logging, alerting, and observability for data pipelines.
Role & Responsibilities
- Lead Data Engineer
- What You’ll Do
- Lead the design, development, and maintenance of scalable ETL/ELT pipelines and data products in multi-cloud, multi-region, distributed environments.
- Define and apply appropriate data engineering patterns and architectures based on business and technical requirements.
- Drive technical investigations and resolve complex data, operational, and production issues.
- Design scalable, flexible, efficient, and supportable solutions using appropriate technologies and disciplined development practices.
- Provide technical leadership, guidance, and mentorship to data engineering teams.
- Collaborate with architects, engineering teams, and business stakeholders to deliver robust data solutions.
- Key Skills
- Data Engineering & Architecture: Strong understanding of data engineering patterns and modern architectures such as Data Mesh, Data Fabric, Data Lake, and Data Warehouse.
- Big Data & Cloud: Proficiency in Amazon EMR, AWS Glue, Data Lake, and technologies for processing large datasets.
- Programming: Strong proficiency in Python, Java, or Scala, with solid OOP expertise.
- Data Warehousing: Strong knowledge of data warehousing solutions, preferably Snowflake.
- ETL/ELT & Orchestration: Hands-on experience with ETL/ELT pipelines and data orchestration tools.
- Databases: Strong expertise in relational and NoSQL databases.
- Data Modelling: Experience designing efficient OLAP and OLTP data models.
- Streaming: Knowledge of streaming data technologies and architectures.
- Version Control: Experience with Git and modern development practices.
- Containers & Orchestration: Understanding of Docker and Kubernetes.
- Data Security: Knowledge of encryption, access control, data privacy, and compliance.
- Monitoring & Logging: Experience implementing monitoring, logging, alerting, and observability for data pipelines.
Skills Required
- 5-10 years of professional experience
- Strong understanding of data engineering patterns and architectures, including Data Mesh, Data Fabric, Data Lake, and Data Warehouse
- Proficiency with Amazon EMR and AWS Glue
- Strong proficiency in Python, Java, or Scala with object-oriented programming expertise
- Strong knowledge of data warehousing solutions
- Hands-on experience with ETL/ELT pipelines and data orchestration tools
- Strong expertise with relational and NoSQL databases
- Experience designing OLAP and OLTP data models
- Knowledge of streaming data technologies and architectures
- Experience with Git and modern development practices
- Understanding of Docker and Kubernetes
- Knowledge of encryption, access control, data privacy, and compliance
- Experience implementing monitoring, logging, alerting, and observability for data pipelines
- Knowledge of Snowflake
What We Do
IBS Software is a leading SaaS solutions provider to the travel industry globally, managing mission-critical operations for customers in the aviation, tour & cruise, hospitality and energy resources industries. IBS Software's solutions for the aviation industry cover fleet and crew operations, aircraft maintenance, passenger services, loyalty programs, staff travel & air-cargo management. IBS Software also runs a real-time B2B and B2C distribution platform providing hotel room inventory, rates, and availability to a global network of hospitality companies and channels. For the tour and cruise industry, IBS provides a comprehensive customer-centric, digital platform that covers onshore, online and on-board solutions. The Consulting and Digital Transformation (CDx) business focuses on driving digital transformation initiatives of its customers, leveraging its domain knowledge, digital technologies and engineering excellence. IBS Software operates from 16 offices across the world.








