Lead data engineer (Cloud)

Job Description:  

We, at Jet2 (UK’s third largest airlines and the largest tour operator), have set up a state-of-the-art Technology and Innovation Centre in Pune, India. We are recruiting for an experienced and passionate Lead Data Engineer to join our growing Data Engineering program which is focused on making data assets from across our business available in cloud for advanced analytics, data science and automated decision making. These data assets drive mission critical processes across our commercial and operational teams contributing towards profitable growth, competitive advantage, and exceptional customer satisfaction. This is an exciting opportunity to help us become a leading data-driven organisation through the effective use of data. 

The successful candidate will play a pivotal role in the success of our Data Analytics and Engineering program working closely with colleagues across our business and technical teams. You will be designing and building complex data ingestion pipelines from different Jet2 and third party source systems will ensure data is cleansed, well structured, and appropriately transformed into our data lake to support a wide variety of use cases ranging from self-service analytics through to data warehousing and data science. 

Key Responsibilities: 

The successful candidate will be in a lead role with responsibility for both solution delivery and direct management of a team of up to 6-7 Data and QA Engineers (across Senior, Mid, Junior and Graduate levels). They will own delivery commitments for the team, run sprint planning and execute prioritisation order set by Product team, conduct performance reviews and 1:1s, and collaborate closely with stakeholders in Pune and Leeds UK. 

• Design and deliver scalable and reliable data ingestion pipelines to support data consumers across Jet2.com and Jet2Holidays 
• Ingest, cleanse and transform data from a wide variety of sources systems into our cloud data lake to support advanced analytics, data warehousing and data science 
• The primary focus is: 
  ingest data → cleanse data → apply light transformations → make data ready for downstream analytics teams. 

Below are the main areas of responsibility for this role -  

• Data Ingestion  
• Build and maintain data ingestion pipelines from multiple source systems into the cloud data platform. Ingest data from databases, APIs, files, event streams, and third-party systems.  

Support batch, near-real-time, and real-time ingestion patterns where required.  

• Ensure ingestion jobs are reliable, monitored, and recoverable in case of failure.  
• Work with source systems owners / Architect’s teams to understand data availability, structure, refresh frequency, and extraction constraints.  

Data Cleansing and Standardisation  

• Apply basic data cleansing rules and standardization as part of ingestion. 
• Implement basic validation checks to ensure data completeness, accuracy, and consistency.  
• Identify and raise data quality issues with source system owners or relevant stakeholders.  
• Maintain reusable cleansing patterns and standards across ingestion pipelines.  

Light Data Transformation  

• Perform simple transformations to achieve standard data platform formats. Conversion from semi-structured to structured data. 
• Create clean, structured, and well-organised staging or curated datasets.  
• Avoid complex business logic, KPI definitions, semantic modelling, or advanced analytics transformations unless clearly assigned.  

Ingestion Pipeline Development and Maintenance  

• Develop, test, deploy, and maintain optimized data ingestion pipelines using approved cloud data engineering tools.  
• Ensure pipelines follow engineering standards for code quality, configuration, logging, and error handling.  
• Monitor pipeline performance and resolve failures or data load issues.  
• Support pipeline scheduling, orchestration, and dependency management.  
• Data quality reconciliation checks, monitoring, and incidence management  
• Participate in code reviews, testing, deployment planning, and production support.  
• Work with cloud storage, data warehouse, and data lake technologies. (AWS S3, Snowflake , GCS) 
• Follow Jet2’s data platform standards for data storage, partitioning, naming conventions, access control, and security.  
• Ensure data is stored in appropriate zones such as raw, cleansed, staging, or curated layers.  
• Support metadata capture and basic data cataloguing requirements.  
• Follow governance, privacy, and security guidelines while handling enterprise data.  

• Understand in detail Jet2’s current data warehouse architecture and standards (architecture, coding, data modelling etc )  and do detail designing in compliance those and stated business requirement  
• Support the continual training and development of your team and the wider data engineering function at Jet2 to keep up to date with developments in data engineering and drive continual improvement across the team 
• Help to recruit, train and mentor a team of highly skilled Data and QA Engineers with a wide range of technical knowledge and experience 
• Plan, prioritise and oversee end-to-end delivery for the team — managing capacity, sequencing work against business commitments, removing blockers and ensuring quality through robust QA practices 

Technical Skills & Knowledge: 

• Expert-level SQL — advanced query optimisation, window functions, complex joins and performance tuning across large datasets; experience with a variety of source systems including Microsoft SQL Server 
• Cloud Platforms (mandatory): You should have experience working with key services on AWS (preferred) or GCP / Azure. Key services include following: 
• AWS Data Firehose  
• AWS S3 / Data Lake  
• AWS Lamda  
• AWS SQS SNS  
• AWS Event bridge  
• AWS Step Function  
• AWS Athena  
• AWS DynamoDB  
• AWS CloudWatch  
• AWS MWAA (Amazon Managed Workflows for Apache Airflow) 
• Apache Kafka  
• AWS API Gateway  
• Terraform  
• Deep expertise in Snowflake — warehouse sizing and cost optimisation, RBAC, micro-partitioning, clustering keys, Time Travel, Streams & Tasks, Snowpipe, and zero-copy cloning 
• Experience working with DBT to develop, test, deploy and monitor data transformation code 
• Ability to use the AI Tooling @Jet2 (Snowflake Cortex Code, GitHub copilot, AWS Kiro etc.) to effectively to deliver faster value to business by rolling out data products to business 
• Experience working with Infrastructure as Code (IaC), specifically with Terraform (equivalent experience with similar technology also accepted) Develop and maintain Terraform scripts/modules to provision and manage cloud data engineering infrastructure. 
• Experience of working in an Agile delivery team using automated build, deployment and testing (CI\CD, DevOps, DataOps) 
• Experience with one or more programming language compatible with developing functionality on the above platform (Python or Java preferred) 
• Data Visualisation tool (Tableau) knowledge is a plus 

Soft Skills: 

• Excellent communication skills – verbal and written 
• Strong team and stakeholder management skills – you should have the ability to build strong relationships with people across a wide variety of teams and backgrounds 
• Experience working with people across different geographical regions, particularly UK (Leeds and Sheffield) and India (Pune) 
• Excellent planning and time management skills to ensure projects are delivered on time and to requirement with issues being escalated and addressed effectively 
• Exceptional documentation and presentation skills – you will be responsible for documenting solution designs for presentation and sign-off as well as delivering internal presentation to support continual development of your team 

Leadership & Organisation Skills: 

• Lead a team of 6 Data and QA Engineers (Senior, Mid, Junior level) working across multiple projects, with full accountability for delivery, quality and team development 
• Set individual development goals, monitor, and manage performance, provide timely feedback and take responsibility for professional development of team members 
• Collaborate with wider data team including Solution Architects, Specialists, Enterprise Architects, Data Scientists, Data Visualisation Specialists, Analytics Engineers and Test Engineers 

Qualification & Certification: 

• B.E./B.Tech/ MTech in IT or Computer Science from reputed institute (preferred) or master’s degree in quantitative Subjects e.g. Mathematics, Statistics & Economics 
• Any certification or formal training in the following areas would also be highly beneficial: 
• AWS Clod  
• GCP Cloud OR Azure  
• Terraform 
• Cloud Certification in AWS/GCP with the following being preferred  
• Cloud Architect 
• Cloud Data Engineer