Why This Role Stands Out
This hybrid role offers an exciting opportunity to leverage your Quantexa expertise on impactful, large-scale data transformation programs with a globally renowned consultancy. If you thrive in a high-performing team environment, possess strong big data, Spark, and cloud skills, and are seeking a challenging and rewarding contract, this is a fantastic chance to advance your career. Apply today to join this innovative team and contribute to cutting-edge data solutions.
Quick Overview
Job Description
Senior Data Engineer (Quantexa)
Location: London (Hybrid, 2 days in Office per week)
Duration: 6 months +
Rate: Up to £650 per day (Inside IR35)
Opus have partnered with a Globally Renowned Data & AI consultancy who're searching for a Quantexa contractor to help with the delivery of market-leading big data driven transformation programmes.
You'll be joining a high-performing team led by experienced data and AI practitioners who work across solution architecture, advanced analytics, cloud transformation, and multi-million-pound client engagements.
Key Responsibilities:
- Design and build scalable big data pipelines using Quantexa
- Develop and optimise ETL/ELT processes for high-volume, complex datasets.
- Deliver entity resolution and network analytics solutions using Quantexa.
- Integrate data from multiple structured and unstructured sources across enterprise platforms.
- Build data solutions within cloud-native environments (GCP, AWS, Azure).
- Ensure data quality, governance, lineage, and security standards are met, supporting solution design for large-scale data transformation programmes.
Essential Skills
- MUST HAVE: Strong hands-on experience with Quantexa implementation and development.
- Proven experience building and supporting big data platforms.
- Advanced knowledge of Apache Spark / PySpark.
- Strong programming skills in Scala and/or Python.
- Expertise in SQL and large-scale data modelling.
- Strong cloud experience across GCP, AWS, or Azure.
- Experience with Databricks, Snowflake, or Hadoop ecosystems.
- Knowledge of data ingestion, ETL/ELT frameworks, and batch/real-time processing.
Applications are now open.
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