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We are seeking an experienced Data Engineer to design, build, and optimize scalable data platforms that support analytics, reporting, and data-driven decision-making across the organization. This role will partner closely with Product, Analytics, Data Science, and Engineering teams to develop reliable, high-performance data solutions and drive best practices in modern data engineering.

Key Responsibilities

Design and maintain scalable ELT/ETL pipelines using SQL, Python, dbt, and cloud-native technologies.Build and optimize data warehouse and lakehouse solutions leveraging Snowflake, Databricks, and AWS services.Develop dimensional data models and analytics-ready datasets to support business intelligence and advanced analytics.Implement data quality, monitoring, and observability frameworks to ensure data reliability and trust.Build and support batch and near-real-time data pipelines using Kafka, Spark, and Airflow.Optimize platform performance, scalability, and cost across data infrastructure and workloads.Collaborate with cross-functional stakeholders to translate business requirements into scalable data solutions.Drive CI/CD, infrastructure-as-code, and engineering best practices across the data platform.Mentor junior engineers and contribute to technical leadership, architecture decisions, and code reviews.

Required Skills

8+ years of experience in Data Engineering or related fields.Advanced SQL and Python development experience.Strong expertise with Snowflake, dbt, Airflow, and modern ELT frameworks.Experience designing dimensional models and enterprise-scale data warehouses.Hands-on experience with Kafka, Spark/PySpark, and streaming data architectures.Strong understanding of cloud platforms, particularly AWS.Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.Knowledge of data governance, schema evolution, data quality, and observability practices.

Qualifications

Experience supporting analytics, product, marketplace, ecommerce, or customer data platforms.Exposure to Databricks and multi-cloud environments.Background partnering with Data Science, Product, and Analytics teams.Master's degree in Mathematics, Computer Science, Engineering, or a related quantitative field.

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

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We are seeking an experienced Data Engineer to design, build, and optimize scalable data platforms that support analytics, reporting, and data-driven decision-making across the organization. This role will partner closely with Product, Analytics, Data Science, and Engineering teams to develop reliable, high-performance data solutions and drive best practices in modern data engineering.

Key Responsibilities

Design and maintain scalable ELT/ETL pipelines using SQL, Python, dbt, and cloud-native technologies.Build and optimize data warehouse and lakehouse solutions leveraging Snowflake, Databricks, and AWS services.Develop dimensional data models and analytics-ready datasets to support business intelligence and advanced analytics.Implement data quality, monitoring, and observability frameworks to ensure data reliability and trust.Build and support batch and near-real-time data pipelines using Kafka, Spark, and Airflow.Optimize platform performance, scalability, and cost across data infrastructure and workloads.Collaborate with cross-functional stakeholders to translate business requirements into scalable data solutions.Drive CI/CD, infrastructure-as-code, and engineering best practices across the data platform.Mentor junior engineers and contribute to technical leadership, architecture decisions, and code reviews.

Required Skills

8+ years of experience in Data Engineering or related fields.Advanced SQL and Python development experience.Strong expertise with Snowflake, dbt, Airflow, and modern ELT frameworks.Experience designing dimensional models and enterprise-scale data warehouses.Hands-on experience with Kafka, Spark/PySpark, and streaming data architectures.Strong understanding of cloud platforms, particularly AWS.Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.Knowledge of data governance, schema evolution, data quality, and observability practices.

Qualifications

Experience supporting analytics, product, marketplace, ecommerce, or customer data platforms.Exposure to Databricks and multi-cloud environments.Background partnering with Data Science, Product, and Analytics teams.Master's degree in Mathematics, Computer Science, Engineering, or a related quantitative field.

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

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We are seeking an experienced Data Engineer to design, build, and optimize scalable data platforms that support analytics, reporting, and data-driven decision-making across the organization. This role will partner closely with Product, Analytics, Data Science, and Engineering teams to develop reliable, high-performance data solutions and drive best practices in modern data engineering.

Key Responsibilities

Design and maintain scalable ELT/ETL pipelines using SQL, Python, dbt, and cloud-native technologies.Build and optimize data warehouse and lakehouse solutions leveraging Snowflake, Databricks, and AWS services.Develop dimensional data models and analytics-ready datasets to support business intelligence and advanced analytics.Implement data quality, monitoring, and observability frameworks to ensure data reliability and trust.Build and support batch and near-real-time data pipelines using Kafka, Spark, and Airflow.Optimize platform performance, scalability, and cost across data infrastructure and workloads.Collaborate with cross-functional stakeholders to translate business requirements into scalable data solutions.Drive CI/CD, infrastructure-as-code, and engineering best practices across the data platform.Mentor junior engineers and contribute to technical leadership, architecture decisions, and code reviews.

Required Skills

8+ years of experience in Data Engineering or related fields.Advanced SQL and Python development experience.Strong expertise with Snowflake, dbt, Airflow, and modern ELT frameworks.Experience designing dimensional models and enterprise-scale data warehouses.Hands-on experience with Kafka, Spark/PySpark, and streaming data architectures.Strong understanding of cloud platforms, particularly AWS.Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.Knowledge of data governance, schema evolution, data quality, and observability practices.

Qualifications

Experience supporting analytics, product, marketplace, ecommerce, or customer data platforms.Exposure to Databricks and multi-cloud environments.Background partnering with Data Science, Product, and Analytics teams.Master's degree in Mathematics, Computer Science, Engineering, or a related quantitative field.

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

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We are seeking an experienced Data Engineer to design, build, and optimize scalable data platforms that support analytics, reporting, and data-driven decision-making across the organization. This role will partner closely with Product, Analytics, Data Science, and Engineering teams to develop reliable, high-performance data solutions and drive best practices in modern data engineering.

Key Responsibilities

Design and maintain scalable ELT/ETL pipelines using SQL, Python, dbt, and cloud-native technologies.Build and optimize data warehouse and lakehouse solutions leveraging Snowflake, Databricks, and AWS services.Develop dimensional data models and analytics-ready datasets to support business intelligence and advanced analytics.Implement data quality, monitoring, and observability frameworks to ensure data reliability and trust.Build and support batch and near-real-time data pipelines using Kafka, Spark, and Airflow.Optimize platform performance, scalability, and cost across data infrastructure and workloads.Collaborate with cross-functional stakeholders to translate business requirements into scalable data solutions.Drive CI/CD, infrastructure-as-code, and engineering best practices across the data platform.Mentor junior engineers and contribute to technical leadership, architecture decisions, and code reviews.

Required Skills

8+ years of experience in Data Engineering or related fields.Advanced SQL and Python development experience.Strong expertise with Snowflake, dbt, Airflow, and modern ELT frameworks.Experience designing dimensional models and enterprise-scale data warehouses.Hands-on experience with Kafka, Spark/PySpark, and streaming data architectures.Strong understanding of cloud platforms, particularly AWS.Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.Knowledge of data governance, schema evolution, data quality, and observability practices.

Qualifications

Experience supporting analytics, product, marketplace, ecommerce, or customer data platforms.Exposure to Databricks and multi-cloud environments.Background partnering with Data Science, Product, and Analytics teams.Master's degree in Mathematics, Computer Science, Engineering, or a related quantitative field.

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

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We are seeking an experienced Data Engineer to design, build, and optimize scalable data platforms that support analytics, reporting, and data-driven decision-making across the organization. This role will partner closely with Product, Analytics, Data Science, and Engineering teams to develop reliable, high-performance data solutions and drive best practices in modern data engineering.

Key Responsibilities

Design and maintain scalable ELT/ETL pipelines using SQL, Python, dbt, and cloud-native technologies.Build and optimize data warehouse and lakehouse solutions leveraging Snowflake, Databricks, and AWS services.Develop dimensional data models and analytics-ready datasets to support business intelligence and advanced analytics.Implement data quality, monitoring, and observability frameworks to ensure data reliability and trust.Build and support batch and near-real-time data pipelines using Kafka, Spark, and Airflow.Optimize platform performance, scalability, and cost across data infrastructure and workloads.Collaborate with cross-functional stakeholders to translate business requirements into scalable data solutions.Drive CI/CD, infrastructure-as-code, and engineering best practices across the data platform.Mentor junior engineers and contribute to technical leadership, architecture decisions, and code reviews.

Required Skills

8+ years of experience in Data Engineering or related fields.Advanced SQL and Python development experience.Strong expertise with Snowflake, dbt, Airflow, and modern ELT frameworks.Experience designing dimensional models and enterprise-scale data warehouses.Hands-on experience with Kafka, Spark/PySpark, and streaming data architectures.Strong understanding of cloud platforms, particularly AWS.Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.Knowledge of data governance, schema evolution, data quality, and observability practices.

Qualifications

Experience supporting analytics, product, marketplace, ecommerce, or customer data platforms.Exposure to Databricks and multi-cloud environments.Background partnering with Data Science, Product, and Analytics teams.Master's degree in Mathematics, Computer Science, Engineering, or a related quantitative field.

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

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Step into a high‑impact engineering role where you'll shape the future of Microsoft SQL operations at enterprise scale. As a Database SRE, you'll combine deep SQL Server expertise with modern SRE practices to build a more reliable, automated, and observable database platform for one of the world's largest financial institutions.

What You'll Do

Lead SQL Engineering - Solve complex SQL Server 2016-2022 challenges across availability, tuning, performance, and architecture.

Shape the MSSQL SRE practice - Influence standards, patterns, SLIs/SLOs, and operational models for the SQL estate.

Act as the top technical escalation - Provide expert‑level guidance on incidents, root cause, and long‑term fixes.

Drive automation and standardisation - Reduce TOIL through scripting, configuration management, and platform engineering.

Enhance observability - Improve monitoring, alerting, telemetry, and reliability insights across the estate.

Collaborate across engineering - Work with product, engineering, and platform teams to deliver resilient, scalable database services.

What You'll Bring

Deep Microsoft SQL Server expertise (SQL 2016-2022) across performance tuning, HA/DR, internals, and enterprise‑scale architecture.

Strong SRE mindset - SLIs/SLOs, error budgets, automation‑first thinking, and reliability engineering.

Hands‑on automation skills using PowerShell, T‑SQL, and scripting for migrations, deployments, and operational tooling.

Expertise with configuration management tools such as Chef or Ansible for database server builds and standardisation.

Experience reducing TOIL through simplification, automation, and self‑service patterns.

Ability to influence change across risk, controls, transformation, and digital engineering domains.

GCS is acting as an Employment Agency in relation to this vacancy.

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

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Job Role: Data Science Engineer

Job Type: Contract (Inside IR35)

Location: Reading, UK (2-3 days/week)

Job Description

5+ years of advanced SQL expertise, with a strong track record in querying, cleansing, integrating, and analysing complex datasets at scale, ideally within Databricks environments.Strong Python capabilities for data manipulation, statistical analysis, and predictive modelling.Demonstrated success in developing, validating, and continuously optimising data science models that directly contribute to revenue growth and commercial performance.Experience with propensity modelling and related predictive analytics techniques is highly advantageous.Exceptional ability to translate complex analytical findings into clear, compelling insights for senior stakeholders and cross-functional audiences.Strong analytical thinking and problem-solving skills, with proven success operating in fast-paced, high-growth environments with evolving business priorities.

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

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Data Engineer - AWS
Contract: 12 Months
Location: London (Liverpool Street)
Start Date: 1 June

A global enterprise organisation within sustainability and operations is seeking an experienced AWS Data Engineer for a 12‑month contract based in London.

This is a hands‑on role focused on building and supporting data infrastructure used for energy, utilities and sustainability analytics across large‑scale operations.

Key responsibilities:

Designing and building AWS‑based data pipelines (Lambda, Glue, S3)Developing and maintaining API integrations with external vendorsSupporting analytics dashboards and reporting use casesImplementing automated alerting and anomaly detectionWorking with utility billing, smart metering and sustainability dataEnsuring compliance with enterprise security and data governance standards

Required skills & experience:

Strong hands‑on AWS data engineering experienceAdvanced Python and SQLExperience building production data pipelines and integrationsBackground working in large enterprise environmentsUtilities, energy or sustainability experience highly desirable

Additional details:

Onsite: 4-5 days per weekInterview process: One stage, interviewing immediatelyOnboarding: Fast turnaround (2 references required)

Apply now for immediate consideration.

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

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DATA INTEGRATION ENGINEER (BANKING) - CONTRACT

London | Hybrid (5 days in 10 on-site) 6 Months | Inside IR35£700 Per Day | Umbrella

THE PROJECT

A global banking organisation is expanding its data integration capability and needs a technically strong contractor who can manage complex data environments, support regulatory reporting, and build scalable integration solutions across critical platforms. If you enjoy solving data challenges, improving data quality, and working across enterprise systems-this role is for you.

Design, build, and support enterprise-grade data integration and transformation solutions.Work across SQL Server and Oracle environments to manage large-scale data processing.Develop and maintain ETL pipelines, data marts, and reporting datasets.Support regulatory and banking reporting requirements with accurate, reliable data flows.Ensure strong standards across data quality, security, governance, and compliance.Collaborate with technical and non-technical stakeholders across IT and business teams.Contribute to platform optimisation, tooling improvements, and integration best practices.Support ongoing delivery across cloud and enterprise data platforms.

SKILLS NEEDED

Strong hands-on experience with SQL Server, Oracle, and ETL tooling.Deep understanding of PL/SQL, TSQL, data integration, and transformation.Experience with ETL and integration tools such as DataStage, SSIS, or Alteryx.Strong analytical and problem-solving skills across complex data environments.Excellent communication skills with both technical and business stakeholders.Experience within banking or regulatory reporting environments.Bonus: exposure to Azure, Databricks, Kafka, Middleware, or ECB/AQR reporting.

YOUR IMPACT

Your work will directly support critical banking data operations, regulatory reporting, and enterprise integration initiatives. You'll help improve the reliability and scalability of key data platforms while partnering with senior technology and business stakeholders across a major financial services environment.

Sound good? Apply ASAP - this opportunity is expected to move quickly.

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

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