Senior Data Analytics Engineer

easyJet Airline Company PLC
London
2 months ago
Applications closed

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Job Description

Description

Luton/Hybrid

COMPANY

When it comes to innovation and achievement there are few organisations with a better track record. Join us and you’ll be able to play a big part in the success of our highly successful, fast-paced business that opens up Europe so people can exercise their get-up-and-go. With almost 300 aircraft flying over 1,000 routes to more than 32 countries, we’re the UK’s largest airline, the fourth largest in Europe and the tenth largest in the world. Set to fly more than 90 million passengers this year, we employ over 10,000 people. It’s big-scale stuff and we’re still growing.

JOB PURPOSE

The Senior Analytics Engineer leads the development and optimisation of our advanced analytics ecosystem, ensuring that data is not only fit for purpose but also robustly designed for scalability, reusability, and actionable insights. This role bridges technical expertise and strategic vision to deliver enterprise-grade data solutions, supporting high-impact business use cases across multiple domains.

JOB ACCOUNTABILITIES

To shape and manage future direction of easyJet’s Data Engineering practice, focused on defining, designing and deploying critical analytical pipelines supporting high-quality and reusable data assets:

  1. Define and drive the future direction of data engineering and analytics practices, ensuring alignment with business goals and technological advancements.
  2. Design and implement sophisticated data pipelines and transformations, delivering curated, high-quality datasets for advanced analytics, reporting, and AI/ML applications.
  3. Act as a technical leader and mentor to Analytics Engineers, BI Analysts, and Data Scientists, ensuring cohesive methodologies and enhancing organisational data literacy across the business domains.
  4. Serve as a senior technical Data Steward, championing best practices in data governance, discoverability, and usage, while ensuring end-to-end documentation and observability of analytical pipelines.
  5. Leads collaboration with BI Analysts and Data Scientists to refine methodologies, enhance reporting, and deliver scalable, production-ready feature engineering code.
  6. Drives engagement with business stakeholders, effectively communicating complex technical concepts in a clear, accessible manner to align analytics engineering initiatives with strategic goals.

Requirements of the Role

KEY SKILLS REQUIRED

The Senior Analytics Engineer manages data flow in the data lakehouse, ensuring well-structured, high-quality data for analysis and strategic decision-making. Key responsibilities include designing scalable data architectures in conjunction with Domain and Product Data Architects, overseeing data pipeline development, and maintaining data integrity. This role involves collaboration with Domain and Business Data Stewards to align data solutions with organizational objectives. Below are the key technical skills needed by a Senior Analytics Engineer:

  1. Advanced SQL expertise is essential for querying, transforming, and managing data within databases to support business insights. Proven experience in developing and optimising ETL/ELT pipelines, particularly with tools like DBT, ensures efficient data transformation and modelling.
  2. A strong understanding of data modelling techniques, including star and snowflake schemas, is critical for structuring data for analysis. Proficiency in cloud platforms, such as AWS and GCP, with hands-on experience in services like Databricks, Redshift, BigQuery, and Snowflake, is highly valued.
  3. Advanced Python skills for data manipulation, automation, and scripting, using libraries like Pandas and NumPy, are necessary for effective data engineering. Expertise in managing and optimising data architectures within data warehouse and lakehouse environments is a core requirement.
  4. Proficiency in version control tools like Git ensures effective collaboration and management of code and data models. Experience with workflow automation tools, such as Apache Airflow, is crucial for streamlining and orchestrating complex data processes.
  5. Skilled at integrating data from diverse sources, including APIs, databases, and third-party systems, ensuring seamless connectivity. A strong commitment to data quality assurance is demonstrated through rigorous validation and monitoring processes throughout the data pipeline.
  6. Strong problem-solving abilities are essential for diagnosing and resolving pipeline issues while optimising performance for scalability. Knowledge of analytics platforms, such as Tableau and ThoughtSpot, ensures compatibility with data visualisation and reporting requirements.

What you’ll get in return

  • Competitive base salary
  • Up to 20% bonus
  • BAYE, SAYE & Performance share schemes
  • Flexible benefits package
  • Excellent staff travel benefits

Apply
Complete your application on our careers site.
We encourage individuality, empower our people to seize the initiative, and never stop learning. We see people first and foremost for their performance and potential and we are committed to building a diverse and inclusive organisation that supports the needs of all. As such we will make reasonable adjustments at interview through to employment for our candidates.

#MP2 #LI-HYBRID

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