Data Engineer – AI & Analytics Platform
| Posting date: | 10 February 2026 |
|---|---|
| Hours: | Full time |
| Closing date: | 06 March 2026 |
| Location: | Ilford, Essex |
| Remote working: | Hybrid - work remotely up to 2 days per week |
| Company: | Datashrubs Technologies Ltd |
| Job type: | Permanent |
| Job reference: |
Summary
We are looking for a Data Engineer to build and scale the data infrastructure, pipelines, and AI-ready architecture powering our global engineering marketplace, revenue intelligence, and product analytics.
This role ensures accurate GMV/revenue data, real-time analytics, and ML/NLP-ready datasets for decision-making and investor reporting.
Key Responsibilities
Design and maintain scalable ETL/ELT pipelines using Python and SQL
Build data warehouse models for revenue, users, and product analytics
Enable ML/NLP workflows with clean, feature-ready datasets
Deliver trusted data to BI dashboards and optimize performance
Implement data quality, security, and governance controls
Required Experience
5+ years in Data Engineering or Analytics Engineering
Strong record of building production-grade pipelines and warehouses
Technical Skills
Python, SQL, data modeling
Airflow/dbt, modern data warehouses (Snowflake/BigQuery/Redshift)
AWS/GCP/Azure cloud environments
Exposure to ML/NLP data preparation and BI tools (Power BI/Tableau/Looker)
This role ensures accurate GMV/revenue data, real-time analytics, and ML/NLP-ready datasets for decision-making and investor reporting.
Key Responsibilities
Design and maintain scalable ETL/ELT pipelines using Python and SQL
Build data warehouse models for revenue, users, and product analytics
Enable ML/NLP workflows with clean, feature-ready datasets
Deliver trusted data to BI dashboards and optimize performance
Implement data quality, security, and governance controls
Required Experience
5+ years in Data Engineering or Analytics Engineering
Strong record of building production-grade pipelines and warehouses
Technical Skills
Python, SQL, data modeling
Airflow/dbt, modern data warehouses (Snowflake/BigQuery/Redshift)
AWS/GCP/Azure cloud environments
Exposure to ML/NLP data preparation and BI tools (Power BI/Tableau/Looker)