At a Glance
- Tasks: Design and maintain scalable data solutions in a cloud-native environment.
- Company: Nextlink, a forward-thinking tech company in London.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Great chance to engage in large-scale enterprise data initiatives.
- Why this job: Join a dynamic team and work with cutting-edge GCP technologies.
- Qualifications: Experience with GCP, data modelling, and strong Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
- Data Engineer with Modelling Experience (DE)
- London, United Kingdom
Nextlink is seeking a skilled Data Engineer with strong modelling experience across data warehouse and graph paradigms.
The ideal candidate is proficient across the GCP data stack, CI/CD pipelines, infrastructure-as-code, and data governance tooling, and can operate independently in a complex cloud-native environment.
Job Description
Role Overview
Nextlink is seeking an experienced
Data Engineer with strong expertise in data warehouse and graph data modelling to design, develop, and maintain scalable data solutions within a cloud-native Google Cloud Platform (GCP) environment.
The successful candidate will possess hands‑on experience across the GCP data ecosystem, modern data engineering frameworks, CI/CD automation, infrastructure-as-code, and data governance practices.
This role requires a self‑driven professional who can collaborate effectively with business and technical stakeholders, translate complex business requirements into robust data solutions, and contribute to the delivery of large‑scale enterprise data initiatives.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and transformation frameworks.
- Build and optimize data processing solutions using Big Query, Dataform, and Python.
- Develop, schedule, and monitor Apache Airflow DAGs within Google Cloud Composer.
- Implement and maintain CI/CD pipelines using Git Lab.
- Create, deploy, and manage Terraform modules for infrastructure provisioning and automation.
- Design and maintain enterprise data models across data warehouse and graph databases.
- Develop and manage Cloud Spanner schemas, queries, indexes, and data structures.
- Implement data governance, metadata management, and data quality practices within Google Cloud.
- Integrate and manage datasets using Google Cloud Storage (GCS), Big Query, Pub/Sub, and associated GCP services.
- Collaborate with solution architects, business analysts, and stakeholders to understand requirements and translate them into technical solutions.
- Support platform scalability, performance optimization, and operational excellence initiatives.
- Participate in code reviews, design reviews, and continuous improvement activities.
- Required Skills & Experience
- Strong hands‑on experience with Google Cloud Platform (GCP).
- Experience designing and managing cloud‑native data platforms.
- Understanding of GCP security, IAM controls, and best practices.
• Experience integrating GCP services including
- Big Query
- Cloud Storage (GCS)
- Cloud Composer
- Pub/Sub
- Cloud Spanner
- Dataform
- SQL & Big Query
• Advanced SQL development skills including
- Window Functions
- Arrays and Structs
- Common Table Expressions (CTEs)
- DDL and DML Operations
- User Defined Functions (UDFs)
- Strong experience with Big Query performance optimization.
• Knowledge of
- Table partitioning and clustering
- Query optimization techniques
- Big Query pricing models (On‑Demand vs Capacity/Slots)
- Experience using Dataform for data transformation and modelling.
- Knowledge of Big Query IAM and security controls.
• Experience implementing
- Data Catalog / Knowledge Catalog
- Metadata management
- Policy tagging
- Data quality frameworks
- Data contracts and governance standards
- Experience consuming APIs and Graph QL services.
- Python Development
- Strong Python programming skills for data engineering and automation.
- Knowledge of Python libraries and frameworks commonly used within cloud data platforms.
The successful candidate must demonstrate strong expertise in
- Data Warehouse Modelling
- Normalization and Denormalization techniques
- Slowly Changing Dimensions (SCD)
- Medallion Architecture
- Business Requirement Analysis and Model Translation
- Apache Airflow / Cloud Composer
- Hands‑on experience creating and managing Apache Airflow DAGs.
- Experience deploying workflows in Google Cloud Composer.
• Integration experience with
- Big Query
- Google Cloud Storage (GCS)
- Dataform
- Knowledge of workflow orchestration, monitoring, troubleshooting, and optimization.
- Experience managing bucket structures and storage design.
• Understanding of
- Storage classes
- Object lifecycle management
- Retention policies
- Knowledge of IAM‑based access management and security controls.
- Strong understanding of source control management.
• Experience with
- Branching strategies
- Merge requests
- Code reviews
- Repository governance
- Hands‑on experience designing and implementing Git Lab CI/CD pipelines.
- Knowledge of automated deployment and testing practices.
- Terraform (Infrastructure as Code)
- Strong understanding of Infrastructure as Code (Ia C) principles.
- Experience developing, maintaining, and deploying Terraform modules.
- Integration of Terraform deployment pipelines with Git Lab.
- Ability to manage cloud infrastructure in a repeatable and scalable manner.
- Experience querying and managing Google Cloud Spanner.
- Strong understanding of relational database design principles.
- Primary key design
- Interleaved tables
- Secondary and global indexes
- Schema optimization
• Understanding of
- Strong consistency reads
- Stale reads
- Distributed database architecture
- Pub/Sub
- Understanding of event‑driven architectures.
- Experience working with Google Cloud Pub/Sub messaging systems.
- Knowledge of real‑time data integration patterns and asynchronous processing.
- GIS / Geospatial Data
- Experience working with GIS and geospatial datasets.
• Understanding of
- Coordinate reference systems
- Coordinate transformations
- Common geospatial data formats
- Experience using Big Query GIS functions and geospatial analytics.
- Domain Knowledge
- Telecommunications (Preferred)
- Experience working within telecommunications environments with understanding of:
- Network assets and inventory
- Performance KPIs
- Telemetry data
- Stakeholder Management
- Proven experience engaging with business and technical stakeholders.
- Ability to communicate complex technical concepts to non‑technical audiences.
- Experience working on large‑scale enterprise transformation and data platform projects.
- Strong problem‑solving, planning, and delivery skills.
- Nice to Have
- Experience with
- Google Dataflow and
- Apache Beam
- Knowledge of streaming data architectures.
- Exposure to graph databases and advanced analytics platforms.
- Experience within highly regulated enterprise environments.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related discipline.
• Relevant Google Cloud certifications will be highly regarded
- Professional Data Engineer
- Professional Cloud Architect
- Associate Cloud Engineer
- #J-18808-Ljbffr
Data Engineer with Modelling Experience (DE) in London employer: NextLink Group
Join a dynamic and innovative team in Slough, where we prioritise employee growth and development in the field of upstream process sciences. Our collaborative work culture fosters creativity and encourages the use of cutting-edge technologies, providing you with unique opportunities to contribute to groundbreaking biologics research. With a strong commitment to quality and compliance, we offer a supportive environment that values your contributions and promotes continuous improvement.
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We think you need these skills to ace Data Engineer with Modelling Experience (DE) in London
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