Next-Link

Data Analyst (DA)

Next-Link City of London, England, United Kingdom

IT Services and IT Consulting · 201-500 employees

13 h ago
data-analyst Senior (5-10 yrs) Contractor United Kingdom
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About the role

The Data Analyst will conduct complex analytical investigations, design semantic data models, and develop business intelligence dashboards to support strategic decision-making. They will collaborate with business, engineering, and data teams to ensure high-quality data solutions and effective reporting frameworks.

What they look for

SQL Google BigQuery Data Modeling GIS Telecommunications Tableau Looker Data Analysis Business Intelligence Semantic Data Modeling Medallion Architecture GraphQL Google Cloud Storage GitLab Geospatial Analytics Data Governance

Requirements

Candidates must have at least 5 years of experience in data analytics with advanced proficiency in SQL and Google BigQuery. A bachelor's degree in a relevant field and strong expertise in data modeling and telecommunications domain knowledge are required.

Full description

Role Overview

Nextlink is seeking a highly skilled and experienced Data Analyst to join our team. The ideal candidate will possess strong expertise in SQL, Google BigQuery, data modeling, GIS data analysis, and telecommunications domain knowledge. This role requires a self-driven professional who can perform complex analytical investigations, design semantic data models, develop business intelligence dashboards, and work closely with stakeholders to deliver actionable insights that support strategic and operational decision-making.

The Data Analyst will collaborate with business, engineering, and data teams to ensure high-quality data solutions, effective reporting frameworks, and accurate interpretation of telecommunications and geospatial data assets.

Key Responsibilities

Data Analysis & Insights

  • Conduct ad-hoc data analysis, root cause investigations, and diagnostic assessments to identify trends, anomalies, and business opportunities.
  • Deliver actionable insights and recommendations to technical and non-technical stakeholders.
  • Perform data validation, profiling, and quality assessments to improve data accuracy and reliability.

Data Modeling & Semantic Layer Development

  • Design, develop, and maintain conceptual, logical, and physical data models.
  • Create and manage semantic data models aligned with business requirements and reporting needs.
  • Implement normalization and denormalization strategies to optimize analytical performance.
  • Design and maintain Slowly Changing Dimensions (SCD) and time-series data models.
  • Apply modern data architecture concepts, including Medallion Architecture, to analytical solutions.

Dashboarding & Reporting

  • Develop, enhance, and maintain interactive dashboards and reports using Tableau and/or Looker.
  • Integrate reporting solutions with Google BigQuery and other enterprise data sources.
  • Ensure dashboard accuracy, usability, and alignment with business KPIs.

Data Platform & Engineering Collaboration

  • Partner with data engineering teams to validate data pipelines and outputs.
  • Support data governance, quality monitoring, and optimization initiatives.
  • Contribute to best practices for data management, documentation, and analytics delivery.

Telecommunications & GIS Analytics

  • Utilize telecommunications domain expertise to analyze network performance, operational KPIs, telemetry data, and asset lifecycle information.
  • Work with GIS datasets, geospatial analytics, and location-based intelligence solutions.
  • Leverage BigQuery GIS functions and spatial data concepts to support business requirements.

Stakeholder Management

  • Collaborate with business leaders, product owners, and technical teams to gather requirements and translate them into analytical solutions.
  • Present findings, insights, and recommendations clearly to diverse stakeholder groups.
  • Manage multiple priorities in a fast-paced project environment while maintaining strong communication and engagement.

Requirements

Required Skills & Experience

SQL & Google BigQuery

  • Advanced proficiency in SQL including: • Window Functions
  • Common Table Expressions (CTEs)
  • Arrays and Structs
  • DDL and DML operations
  • User Defined Functions (UDFs)
  • Strong understanding of Google BigQuery including: • Partitioning and Clustering
  • Query Performance Optimization
  • Cost Management and Pricing Models (On-Demand vs Slots)
  • BigQuery IAM and Access Controls
  • Experience working with GraphQL APIs and data extraction processes.

Data Modeling

  • Strong understanding of: • Data normalization and denormalization
  • Conceptual, logical, and physical data modeling
  • Slowly Changing Dimensions (SCD)
  • Time-series data modeling
  • Semantic layer design and development
  • Medallion Architecture principles
  • Proven ability to translate complex business requirements into scalable data models.

Google Cloud Storage (GCS)

  • Experience managing: • Buckets and object storage structures
  • Storage classes and lifecycle management
  • Retention and archival policies
  • IAM-based access controls

GitLab

  • Proficiency in: • Branch management
  • Code commits and merge requests
  • Version control best practices
  • Repository maintenance and collaboration workflows

Tableau / Looker

  • Experience designing and developing business intelligence dashboards.
  • Strong understanding of data visualization best practices.
  • Ability to connect and optimize reporting solutions using BigQuery data sources.

GIS & Geospatial Analytics

  • Knowledge of GIS concepts and spatial data processing.
  • Experience with: • Coordinate systems and conversions
  • Common GIS file formats
  • Geospatial analytics
  • BigQuery GIS capabilities

Education & Experience

  • Bachelor's degree in Data Analytics, Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related field.
  • 5+ years of experience in Data Analytics, Business Intelligence, or a similar role.
  • Experience working in telecommunications and cloud-based data environments is highly desirable.

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