- 6 month extendable contract
- Remote Working
We are seeking a Data Engineer with strong experience in consumer-facing (B2C) data environments to help build and scale our client's modern data platform. This role will focus on collecting, processing, and transforming customer, product, marketing, and behavioural data into actionable insights that drive business growth.
You will work closely with Product, Marketing, Analytics, and Data teams to develop reliable and scalable data pipelines that power customer analytics, engagement measurement, attribution, experimentation, and business intelligence. The ideal candidate is passionate about understanding customer behaviour, building robust data products, and enabling data-driven decision-making across the organisation.
- Design, develop, and maintain scalable ETL/ELT processes using Python and SQL.
- Build reliable data pipelines that ingest and process data from web, mobile, marketing, and customer platforms.
- Ensure data is available, accurate, and accessible for analytics and reporting.
- Work with large-scale customer and event-level datasets to generate meaningful business insights.
- Ensure event data is accurately captured, validated, and available for downstream analytics use.
- Integrate and manage data pipelines from marketing, acquisition, and advertising platforms.
- Help stakeholders understand customer acquisition performance and marketing ROI.
- 3+ years of experience in Data Engineering.
- Strong proficiency in SQL and Python.
- Experience working with B2C, customer, consumer, product, or marketing data.
- Hands-on experience building and maintaining ETL/ELT pipelines.
- Experience with cloud-based data platforms such as:
- BigQuery
- Snowflake
- Redshift
- Strong understanding of:
- Customer data models
- User engagement analytics
- Conversion funnels
- Retention metrics
- Customer lifecycle analysis
- Experience integrating data from web, mobile, and marketing platforms.
- Familiarity with version control, testing frameworks, and software engineering best practices.
- Experience with GA4, including BigQuery Export.
- Experience with Snowplow event tracking
- Experience with modern transformation frameworks such as dbt.
- Experience with Docker, Kubernetes, or cloud-native deployment environments.
Employer-sourced description · source: halian.com · captured 7h ago
