Next-Link
Data Analyst (DA)

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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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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


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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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