Infoplus Technologies UK Limited
Data Engineer with Modelling Experience
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Role Title Data Engineer with Modelling Experience (DE)
Location: Greater London
Duration: 6 months
How many days in a week: Work from Office. 3 Days Week / Office
Role Overview
We are seeking a skilled Data Engineer with strong modelling experience across data warehouse and graph paradigms. The ideal candidate is proficient across the GCP data stack, CI/CD pipelines, infrastructure-as-code, and data governance tooling, and can operate independently in a complex cloud-native environment.
Key Responsibilities
- Design, build, and maintain scalable data pipelines and transformation workflows
- Implement and manage CI/CD pipelines within GitLab
- Deploy and maintain Terraform modules for repeatable infrastructure provisioning
- Develop and orchestrate Airflow DAGs in Google Cloud Composer
- Model data at warehouse and graph levels to support platform requirements
- Manage SpannerDB schema design and querying
- Apply BigQuery knowledge catalog and data governance practices
- Collaborate with stakeholders and contribute to large-scale project delivery
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Required Skills & Experience
SQL & BigQuery
- Advanced SQL (window functions, arrays and structs, DDL, DML, UDFs, CTEs)
- Dataform for SQL modelling and transformation tasks
- BigQuery computational model — partitioning, clustering, query optimisation, pricing model (on-demand vs slots)
- Knowledge Catalog integrations: CDE identification, metadata, policy tagging, data quality scans (Data Contracts)
- Understanding of BigQuery IAM access principles
- Experience using GraphQL
Python
- Proficient Python development for data engineering tasks
Data Modelling
- Data warehouse and graph modelling
- Normalisation and denormalisation
- Conceptual, logical, and physical modelling
- SCD and time series modelling
- Medallion architecture concept
- Translation of business requirements into modelling outputs
Airflow / Composer
- DAG creation and execution
- Utilising Airflow in a cloud environment
- Integration with GCS, BigQuery, and Dataform
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GCS (Google Cloud Storage)
- Bucket and blob structure
- Storage classes and retention policies
- Bucket access management via IAM
GitLab
- Branch management, commits, merges, repository maintenance
- CI/CD pipeline setup and execution in GitLab
Terraform (IaC)
- Terraform fundamentals and GitLab integration
- Deploying and modifying repeatable modules
SpannerDB
- Querying Spanner databases
- Relational modelling and schema design (primary keys, interleaved/global indexes)
- Use of interleaved tables, strong vs stale reads
Pub/Sub
- Understanding of event-driven messaging with Pub/Sub
GIS Data
- Knowledge of GIS data and engines (coordinate conversions, common file formats, BigQuery GIS)
Domain Knowledge
- Telecommunications: network topology, KPIs, telemetry, asset lifecycle
Stakeholder Management
- Proven experience in stakeholder engagement on large-scale projects
Nice to Have
- Dataflow (Apache Beam)
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