Senior Data Engineer

Travel Chapter

Senior Data Engineer building Travel Chapter’s data platform for holiday experiences. Designing pipelines, warehouses and reliable datasets for analytics, operations and data products.

Posted 9/2/2026full-timeBideford • 🇬🇧 United KingdomSenior💰 £50,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining data pipelines, ETL processes, and data models, with a strong focus on SQL and Python for data engineering. Proven ability to optimize data solutions for performance and reliability while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Data Engineering ExperienceAdvanced SQL SkillsStrong Python SkillsCloud Data Warehouse ExperienceData Quality and Reliability

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignETL ProcessesData ModellingDatabase Schema DesignAutomated TestingVersion ControlCI/CDPerformance DiagnosisData Quality ProcessesTechnical Documentation

Soft Skills

Excellent Communication SkillsMentoring and Coaching

Tools & Technologies

SnowflakeBigQueryRedshiftAWSGlueMySQLSQL ServerDbtFivetranJSON

Industry Keywords

Data WarehousingDimensional ModellingData IntegrationObservabilityTechnical Debt

Tech Stack

Tools & technologies

Amazon RedshiftAWSBigQueryCloudETLMySQLPythonSQL

About the role

Key responsibilities & impact

Design, build and maintain data pipelines, ETL processes and data models
Make and document architectural and data-modelling decisions
Integrate and transform diverse data sources into a reliable, unified data platform
Design and implement database schemas for large volumes of structured and unstructured data
Build scalable and maintainable data solutions supporting analytics, reporting, operational processes and data-driven products
Champion engineering standards across SQL, Python, testing, documentation and code review
Review designs and code produced by other engineers
Identify and address technical debt and improve the data platform
Optimise data solutions using partitioning, indexing and caching
Develop and maintain data quality processes
Improve reliability, observability and performance of data solutions
Collaborate with product managers, developers, data colleagues and business stakeholders to define requirements
Diagnose and resolve performance and production issues
Coach and mentor engineers
Keep up to date with data engineering developments and evaluate new technologies
Participate in the team’s out-of-hours support rota where required

Requirements

What you’ll need

Strong commercial data engineering experience, ideally in a senior or lead capacity
Significant experience delivering production data engineering solutions
Advanced SQL and an excellent understanding of databases
Strong Python skills for data engineering
Strong understanding of data warehousing and dimensional/data modelling
Experience designing and operating production data pipelines
Experience with a modern cloud data warehouse such as Snowflake, BigQuery or Redshift
Experience with automated testing, version control and CI/CD
Strong understanding of data quality, reliability and observability
Experience diagnosing performance and production issues
Ability to make, document and communicate technical design decisions
Experience mentoring or supporting other engineers
Excellent written and verbal communication skills
Desirable: Experience with Snowflake, dbt or Fivetran
Desirable: Experience working with AWS / Glue
Desirable: Experience with MySQL or SQL Server
Desirable: Experience with Salesforce
Desirable: Familiarity with JSON and data integration formats

Benefits

Comp & perks

Opportunity to influence the direction of the data platform
Collaborative product environment
Learning and professional development through coaching, mentoring, knowledge sharing, and evaluating new technologies
Work with a broad range of technologies
B Corp certified, people-first business
Participation in an out-of-hours support rota where required, in accordance with agreed support arrangements and SLAs