Infinity Quest
Data Engineer
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Role: Data Engineer/Analyst
Location: London, UK
Mode: Hybrid
Type: Contract
Contact Details: +48 528808909 / vijay.kumar@i-q.co
Job Description:
Role Overview
We are looking for an experienced Data Engineer with strong expertise in data modelling across data warehouse and graph paradigms. The ideal candidate should be proficient in the GCP data stack, CI/CD, Infrastructure as Code (IaC), data governance, and cloud-native data engineering.
The role requires someone who can work independently in a complex environment and contribute to large-scale data engineering initiatives.
Key Responsibilities
- Design, build, and maintain scalable data pipelines and transformation workflows.
- Develop and manage CI/CD pipelines using GitLab.
- Build and maintain Terraform modules for repeatable infrastructure provisioning.
- Develop and orchestrate Airflow DAGs using Google Cloud Composer.
- Perform data warehouse and graph modelling to support business and platform requirements.
- Design and manage SpannerDB schemas and queries.
- Apply BigQuery data governance, cataloguing, and data quality practices.
- Collaborate with technical and business stakeholders on large-scale projects.
Required Skills & Experience
SQL & BigQuery
- Advanced SQL including window functions, arrays/structs, DDL, DML, UDFs, and CTEs.
- Strong experience with BigQuery partitioning, clustering, query optimization, and pricing models.
- Experience with Dataform for SQL modelling and transformation.
- Knowledge of data cataloguing, metadata management, policy tagging, data quality scans, and Data Contracts.
- Understanding of BigQuery IAM and access management.
- Experience with GraphQL.
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Python
- Strong Python development skills for data engineering and automation.
Data Modelling
- Strong experience in data warehouse and graph modelling.
- Knowledge of normalization, denormalization, conceptual, logical, and physical modelling.
- Experience with Slowly Changing Dimensions (SCD) and time-series modelling.
- Understanding of Medallion Architecture.
- Ability to translate business requirements into effective data models.
Airflow / Google Cloud Composer
- Experience creating and managing Airflow DAGs.
- Hands-on experience running Airflow in cloud environments.
- Integration with GCS, BigQuery, and Dataform.
Google Cloud Storage (GCS)
- Understanding of bucket and blob structures.
- Knowledge of storage classes and retention policies.
- Experience managing bucket access using IAM.
GitLab & CI/CD
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- Experience with branching, commits, merges, and repository management.
- Hands-on experience setting up and managing CI/CD pipelines in GitLab.
Terraform / Infrastructure as Code
- Strong understanding of Terraform fundamentals.
- Experience integrating Terraform with GitLab.
- Ability to deploy, modify, and maintain reusable Terraform modules.
SpannerDB
- Experience querying Google Cloud Spanner.
- Knowledge of relational modelling and schema design, including primary keys and interleaved/global indexes.
- Understanding of interleaved tables and strong vs. stale reads.
Pub/Sub
- Understanding of event-driven architectures and Google Cloud Pub/Sub.
GIS Data
- Knowledge of GIS data and spatial data engines.
- Understanding of coordinate conversions, common GIS file formats, and BigQuery GIS.
Domain Knowledge
- Telecommunications
- Experience or understanding of:
- Network topology
- Network KPIs
- Telemetry data
- Asset lifecycle management
- Experience or understanding of:
Stakeholder Management
- Strong communication and stakeholder management skills.
- Proven ability to work with technical and business stakeholders on large-scale data engineering projects.
- Ability to work independently in complex cloud-native environments.
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