Apply to the vacancy...
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Apply to the vacancy...
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Sign up for Jobbird
An error occurred while opening the sign-up page. Please try again.

Loading window...

Forgot my password
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Log out
Unfortunately, something went wrong while signing out. Please try again.

Loading window...

Job application sent
Something went wrong while logging in. Please try again.
Something went wrong while signing up. Please try again.

Loading window...

logo
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
Filters
Filters
Location and distance
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
Jobs posted from
Salary from (per month)
Filters
How our sorting works

The order in which job vacancies are displayed is determined by a composite score based on the following factors:

  • Keyword Relevance: How well your search terms match the vacancy details. We prioritize matches found in the job title, followed by job requirements, location names, and educational levels. Matches within general employer information or the organization's name carry a lower weight.
  • Commercial Prioritization (Premium Jobs): Vacancies paid for by employers ('Premium' or 'Sponsored') receive a ranking boost and will appear higher in the search results.
  • Recency (Date Relevance): Newer vacancies are prioritized. The relevance score of a vacancy is reduced by half once the posting is older than 30 days.
  • Proximity (Distance Relevance): Vacancies located closer to your search location are ranked higher. For vacancies located more than 30 km from the search center, the relevance score is halved.
The final ranking is established by multiplying all these individual factors to calculate the total relevance score.

GCS

Senior Data Engineer

GCS London
600 to 850
32 - 40 hour


Show Recently closed jobs

    GCS

    Senior Data Engineer

    GCS London
    600 to 850
    32 - 40 hour
    Status Open
    Apply now

    Apply on the employer's website


    What we ask

    Education

    No minimum education required

    What we offer

    Salary
    £600 to £850
    Hours
    32 to 40 hours per week
    Employment type
    contract

    Job description

    Senior Data Engineer Role (Python / Spark / Databricks) - Hybrid - Contract - Banking

    Role - Senior Data Engineer

    Rate - £850 p/d (Inside IR35)

    Duration - 6 months with very likely extension

    Location - Hybrid / Liverpool Street (London) - 3 days per week in a Liverpool Street office

    About the Role

    Global financial institution seeking a highly skilled Senior Data Engineer to join a growing data engineering function responsible for delivering critical data platforms and analytics capabilities across the business.

    This is a genuinely hands-on engineering role, requiring strong expertise in Python, Databricks, Spark/PySpark and SQL. The successful candidate will be actively involved in the design, development, optimisation and support of enterprise-scale data platforms, working alongside engineers, architects and business stakeholders to deliver robust and scalable solutions.

    The role offers the opportunity to work on complex data challenges within a modern cloud-based environment, leveraging the latest data engineering technologies and best practices.

    Key Responsibilities

    Data Engineering & Development

    Design, develop and maintain scalable data pipelines using Python, Databricks and PySpark
    Build and optimise ETL/ELT solutions processing large-scale datasets
    Develop high-quality, reusable code and engineering frameworks
    Deliver robust, performant and maintainable data solutions
    Troubleshoot and resolve complex production and performance issues
    Support the ongoing enhancement and modernisation of enterprise data platformsDatabricks & Data Platform Engineering

    Develop and support Databricks-based data solutions and Lakehouse architectures
    Utilise Delta Lake and Spark technologies to deliver scalable data processing capabilities
    Optimise distributed data processing workloads for performance and reliability
    Implement data quality controls and monitoring solutions
    Contribute to platform stability, scalability and operational excellenceSolution Delivery

    Work closely with business and technology stakeholders to understand requirements and deliver effective solutions
    Participate in Agile delivery processes including sprint planning, refinement and estimation
    Support the delivery of strategic data initiatives across multiple business areas
    Collaborate with architects, engineers and product teams to deliver high-quality outcomes
    Identify and resolve technical risks and implementation challengesEngineering Best Practice

    Promote software engineering best practices including testing, code reviews and version control
    Support CI/CD adoption and deployment automation
    Contribute to coding standards and engineering governance
    Drive continuous improvement across development and support processes
    Mentor junior engineers and contribute to knowledge sharing within the teamRequired Skills & Experience

    Strong commercial experience as a Data Engineer or Senior Data Engineer
    Expert-level Python development skills
    Extensive hands-on experience with Databricks in enterprise environments
    Strong Apache Spark and PySpark expertise
    Advanced SQL development and optimisation skills
    Experience designing and building large-scale ETL and data integration solutions
    Strong understanding of distributed computing concepts and data processing frameworks
    Experience working with modern cloud platforms including Azure, AWS or GCP
    Knowledge of software engineering principles, testing and code quality practices
    Experience working within Agile development environments
    Excellent problem-solving and troubleshooting capabilitiesDesirable Experience

    Experience within investment banking, financial services or other highly regulated environments
    Exposure to risk, trading, treasury or regulatory data domains
    Experience with Kafka, streaming technologies or real-time data processing
    Databricks certifications
    Experience with Airflow, Databricks Workflows or similar orchestration tools
    CI/CD pipeline development and DevOps practices
    Docker and Kubernetes
    Experience supporting data science or machine learning workloadsThis role will suit a Senior Data Engineer who enjoys remaining close to the technology and has strong recent experience building production-grade solutions using Python, Databricks, Spark/PySpark and SQL in enterprise environments.

    GCS is acting as an Employment Business in relation to this vacancy
    Salary description

    £600.00 - £850.00 per day

    Apply now

    Apply on the employer's website

    Apply now

    Apply on the employer's website


    Vacancy actions

    Save as favorite
    Share vacancy
    Or apply later


    London England

    Jobs

    • Search for jobs
    • Jobs per location
    • Jobs per job profession
    • Jobs per employment
    • Jobs per educational attainment

    Jobbird

    • Switch to different region
    • Terms and Conditions
    © 2026 Jobbird