Data Engineer with Modelling Experience (DE)

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