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

• 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.
  

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