Job Overview

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Job Details

Position: Lead Data Engineer
Location: Pune, Maharashtra
Job Type: Permanent

Company Overview

At Jet2, the UK’s third-largest airline and second-largest tour operator, we’ve established a state-of-the-art Technology and Innovation Center in Pune, India. We're looking for an experienced and passionate Lead Data Engineer to join our growing Data Engineering project. This project focuses on making data resources across our business accessible in the cloud for advanced analytics, data science, and automated decision-making. These data assets drive strategic processes across our business and operations, contributing to efficient growth, competitive advantage, and exceptional customer satisfaction.

This is an exciting opportunity to help us become a leading data-driven organization through the effective use of data. The successful candidate will play a crucial role in the success of our Data Engineering project, working closely with colleagues across our business and technical teams. You will design and build complex data solutions, ensuring data is cleaned, well-organized, and transformed to support a wide variety of use cases, from self-service analytics to data warehousing and data science.

Key Responsibilities

• Design and deliver scalable, reliable data products to support data consumers across Jet2.com and Jet2Holidays.
• Ingest, clean, and transform data from a variety of source systems into our cloud data lake to support advanced analytics, data warehousing, and data science.
• Design data engineering solutions running on various cloud platforms, including Google Cloud and AWS.
• Support continuous training and development of the team and the broader data engineering capability at Jet2 to stay up to date with trends and drive continuous improvement.
• Assist with recruitment, training, and mentoring a team of highly skilled data engineers with a diverse range of technical knowledge and experience.

Technical Skills & Experience

Must Have:

• At least 8 years of experience in Data Engineering or Data Warehouse environments, with hands-on experience working with on-premise VLDBs (Very Large Scale Databases) such as Microsoft SQL Server, Teradata, Oracle, Vertica, Hadoop, etc.
• Strong expertise in SQL is essential.
• At least 3 years of experience working with Snowflake Cloud Data Warehouse—using advanced features to build efficient data engineering pipelines.
• At least 3 years of experience in Cloud Data Engineering on Google Cloud Platform (GCP) or Amazon Web Services (AWS) with hands-on experience in the following services:
  • Cloud Storage (Google Cloud Storage, AWS S3, or similar)
  • Cloud Database Services (Cloud SQL, Firestore, Bigtable, AWS RDS, DynamoDB, Aurora)
  • Cloud Analytics Services (Google BigQuery, AWS Redshift)
  • Cloud Data Integration (Apache Kafka, Google Dataflow/Dataproc, Fivetran, AWS Glue, AWS EMR)
  • Serverless Functions (AWS Lambda, Google Cloud Functions, or equivalent)
  • Apache Airflow (Google Composer or Amazon Managed Workflows for Apache Airflow) including DAG development
  • Kubernetes (Google Kubernetes Engine (GKE), AWS Elastic Kubernetes Service (EKS), or equivalent containerization experience)
• At least 2-3 years of experience with Python programming for advanced data management.
• Experience designing cloud data warehouse and analytics solutions using layered modeling techniques, with knowledge of various strategies like Data Vault.
• Experience working with Infrastructure as Code (IaC), specifically using CI/CD and DevOps/DataOps practices, with tools like Terraform.
• Agile software development mindset and ability to follow strict delivery processes and guidelines.
• Expertise in handling both structured and unstructured data.

Desirable:

• Snowflake Certified (Snowflake Expert or Advanced Certification).
• Cloud certifications such as AWS Certified Data Analytics, AWS Certified Solutions Architect (Associate/Professional), or Google Cloud Certified - Professional Data Engineer.
• Any formal training in Python, Snowflake, DBT, Terraform, or other relevant technologies.

Leadership & Team Management Skills

• Lead a team of data engineers (Senior, Mid, Junior, and Graduate level) to ensure end-to-end delivery is accomplished within committed timelines and quality standards.
• Plan, execute, and manage project tasks, ensuring they are completed on time and within scope.
• Manage emotions effectively, recognizing and influencing colleagues' emotions to maintain strong relationships.
• Resolve conflicts or disagreements within the team or among stakeholders and work towards satisfactory resolutions for all parties.
• Set individual development goals, track and manage performance, provide timely feedback, and take responsibility for the professional development of team members.
• Provide guidance and support to team members to help them grow professionally and improve both their technical and non-technical skills.
• Efficiently manage time to ensure tasks are completed within deadlines while maintaining high quality.

Collaboration & Stakeholder Management

• Collaborate with the broader data team, including solution architects, specialists, enterprise planners, data scientists, data visualization experts, analytics engineers, and test specialists, to deliver high-quality data products.
• Work effectively with cross-functional teams, including business analysts, product owners, data scientists, release management, and operations, to achieve project objectives.
• Keep stakeholders informed about project progress, issues, and risks, with proposed solutions and mitigations.
• Collaborate with colleagues across different geographic regions, especially the UK and US.

Problem Solving & Critical Thinking

• Quickly analyze issues, assess different solutions, and make informed decisions.
• Develop alternative approaches when faced with technical limitations or challenges.

Adaptability & Flexibility

• Be open to change and able to pivot when new challenges or needs arise.
• Willingness to work with legacy on-premises technology to maintain and enhance existing data products for business continuity.

Education & Certifications

• B.E./B.Tech/MTech in IT or Computer Science from a reputed institution (preferred).
• Cloud certifications such as AWS, Azure, or Google Cloud (preferred).
• Additional certifications in Python, Snowflake, DBT, Terraform are highly advantageous.

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