Data Engineer

Arrows; Greater London; On-site; GBP 55,000 - 92,000; Full time

Job summary

Arrows is seeking a Senior Data Engineer for a 6-month contract in the UK, paying up to £500 per day (InsideIR35). The role focuses on ETL, data modelling and data warehousing using Google Cloud, DBT and BigQuery.

You will design scalable data models and distributed pipelines, collaborate with stakeholders, mentor junior engineers and drive DataOps practices across agile squads. An immediate start is preferred.

Qualifications

• Proven experience designing and building complex data models and distributed data pipelines.
• Advanced SQL skills for high-performance data transformation and analysis.
• Solid software and data engineering background including CI/CD and agile collaboration.
• Experience delivering large-scale data warehousing solutions, with dimensional modelling and ETL design in GCP.

Responsibilities

• Build scalable data solutions by designing data models and distributed ETL pipelines.
• Collaborate with stakeholders across business areas to capture requirements and translate them into data solutions.
• Embed DataOps principles and drive engineering best practices across teams and squads.
• Work with tools like Google BigQuery, Python, SQL, and DBT to implement data pipelines and features.
• Mentor and coach team members; deputise for Engineering Manager when needed.
• Collaborate in agile squads to support delivery and align with platform governance.

Skills

Data analysis

SQL mastery

CI/CD

Cloud ETL

DBT

Agile

Mentoring

GCP

Tools

Google BigQuery

DBT

CI/CD tooling

Job description

Data Engineer - ETL - Data Warehousing - SWL - 6 month contract - Paying up to £500 per day (InsideIR35) - Immediate starters

Overview

My client is looking for a Senior Data Engineer who can hit the ground the running and has commercial experience working with ETL and Data Modelling.

What you'll do:

• Build Scalable Data Solutions - Design, build and support Data Models & distributed ETL pipelines using big data technologies on large scale data sets.
• Deliver Impactful Data Features - Collaborate with our many stakeholders from multiple business areas to understand business and data challenges, thereafter, developing requirements, specifications and recommendations related to a proposed solution.
• Champion DataOps & Best Practices - Drive data engineering excellence by embedding DataOps principles and best practices into everything you do - becoming a go-to expert in one or more data domains.
• Solve Real-World Problems with Modern Tools - Tackle complex data challenges using tools like Google BigQuery, Python, SQL, and DBT, with opportunities to experiment and optimise through AI.
• Lead & Mentor - Support and coach team members, sharing knowledge and acting as a role model while deputising for the Engineering Manager when needed.
• Collaborate in Agile Squads- Work effectively across multiple workstream squads embedding as needed to support delivery and provide data engineering expertise.
• Shape the Future of Data at Scale - Act as a bridge between various workstreams and the core SDP engineering organisation ensuring alignment to platform best practices, data governance, and architectural principles
• Support workstream squads onboarding data feeds using contributing to strengthening collaboration and reducing mismatches with upstream systems.

What you'll bring:

• Data Analysis & Engineering Expertise - Proven experience designing and building complex data models and distributed data pipelines, with a strong focus on data analysis, insight generation, and solving real-world business problems at scale.
• SQL Mastery - Advanced SQL skills for high-performance data transformation, exploration, and optimisation across large, complex datasets
• Engineering Best Practices - Solid foundation in software and data engineering, including hands-on experience with CI/CD workflows, test-driven development, and agile collaboration.
• Cloud-Based ETL & Data Warehousing - Demonstrated success delivering large-scale data warehousing solutions, including dimensional modelling and ETL pipeline design-ideally within Google Cloud Platform (GCP) and good working knowledge of DBT (Data Build Tool) for building and managing data pipelines.
• Modelling & Data Flow Understanding - Knowledge of how data is structured, processed, and applied within analytics and reporting environments.
• Incident Support & Operational Readiness - Ability to support the team in diagnosing and resolving data-related incidents, ensuring platform reliability and timely issue resolution