Next-Link
Data Engineer with Modelling Experience (DE)
London
Posted about 17 hours ago
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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 BigQuery, Dataform, and Python.
- Develop, schedule, and monitor Apache Airflow DAGs within Google Cloud Composer.
- Implement and maintain CI/CD pipelines using GitLab.
- 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), BigQuery, 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
GCP Data Engineering
- 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:
- BigQuery
- Cloud Storage (GCS)
- Cloud Composer
- Pub/Sub
- Cloud Spanner
- Dataform
SQL & BigQuery
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- 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 BigQuery performance optimization.
- Knowledge of:
- Table partitioning and clustering
- Query optimization techniques
- BigQuery pricing models (On-Demand vs Capacity/Slots)
- Experience using Dataform for data transformation and modelling.
- Knowledge of BigQuery 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 GraphQL services.
Python Development
- Strong Python programming skills for data engineering and automation.
- Experience developing reusable data processing components.
- Knowledge of Python libraries and frameworks commonly used within cloud data platforms.
Data Modelling
The successful candidate must demonstrate strong expertise in:
- Data Warehouse Modelling
- Graph Data Modelling
- Conceptual Data Modelling
- Logical Data Modelling
- Physical Data Modelling
- Normalization and Denormalization techniques
- Slowly Changing Dimensions (SCD)
- Time-Series Data Modelling
- 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:
- BigQuery
- Google Cloud Storage (GCS)
- Dataform
- Knowledge of workflow orchestration, monitoring, troubleshooting, and optimization.
Google Cloud Storage (GCS)
- 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.
GitLab & CI/CD
- Strong understanding of source control management.
- Experience with:
- Branching strategies
- Merge requests
- Code reviews
- Repository governance
- Hands-on experience designing and implementing GitLab CI/CD pipelines.
- Knowledge of automated deployment and testing practices.
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Terraform (Infrastructure as Code)
- Strong understanding of Infrastructure as Code (IaC) principles.
- Experience developing, maintaining, and deploying Terraform modules.
- Integration of Terraform deployment pipelines with GitLab.
- Ability to manage cloud infrastructure in a repeatable and scalable manner.
Cloud Spanner
- Experience querying and managing Google Cloud Spanner.
- Strong understanding of relational database design principles.
- Expertise in:
- 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 BigQuery GIS functions and geospatial analytics.
Domain Knowledge
Telecommunications (Preferred)
- Experience working within telecommunications environments with understanding of:
- Network topology
- Network assets and inventory
- Performance KPIs
- Telemetry data
- Asset lifecycle management
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
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Skills
Google Cloud Platform
Data Engineering
BigQuery
Data Modelling
Python
Apache Airflow
Terraform
GitLab CI/CD
SQL
Cloud Spanner
Data Governance
Data Warehouse
Graph Databases
Cloud Composer
Dataform
Pub/Sub
Location