CSI GLOBAL LTD
Senior Data Engineer – Python, Databricks
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Senior Data Engineer – Python, Databricks
Bournemouth-UK
Inside IR35
Overview
This role sits within Enterprise Platforms, working on enterprise communication data and scalable data pipelines on the Palmos platform for regulatory controls.
The role involves designing, developing, and maintaining secure, reliable, scalable data solutions supporting business controls, analytics, reporting, and AI/ML use cases.
Job Responsibilities
- Develop workflows and ELT data pipelines using Python, Spark/PySpark, and Databricks
- Onboard enterprise datasets into Palmos, including ingestion, transformation, and validation
- Build, test, and maintain scalable data pipelines and data architectures supporting enterprise controls and analytics use cases
- Build business-control algorithms for communications data to identify anomalies
- Build data completeness and integrity controls for pipelines
- Apply data engineering best practices for performance optimization, reliability, and maintainability
- Use SQL extensively with relational and NoSQL data stores
- Partner with producers to understand data requirements and translate them into production-ready solutions
- Apply SDLC practices, including CI/CD, testing, and operational monitoring
- Contribute reusable frameworks and standards to accelerate onboarding and pipeline delivery
- Identify data issues, anomalies, and optimization opportunities to improve data quality and performance
- Leverage enterprise-authorized AI coding-assist tools to improve code quality, delivery speed, and productivity
- Validate AI-generated outputs through peer review, automated testing, and secure coding standards
- Contribute learnings and reusable patterns to improve broader team effectiveness.
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Required Qualifications, Capabilities & Skills
- Hands-on experience with Databricks, Spark/PySpark, Python, and SQL
- Experience developing and maintaining data pipelines and data-processing systems
- Understanding of the data lifecycle: ingestion, transformation, storage, and consumption
- Knowledge of cloud platforms, including AWS, and distributed data processing
- Experience with SDLC practices including CI/CD, testing, and deployment
- Strong problem-solving skills and ability to troubleshoot data and pipeline issues
- Ability to collaborate effectively within agile teams and across stakeholders
- Hands-on experience using enterprise-authorized AI-assisted software development tools
- Ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
- Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, resiliency, and security expectations
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Preferred Qualifications
- Databricks Lakehouse, Databricks Genie, Delta Lake, and Medallion Architecture
- Familiarity with enterprise data platforms and data mesh principles
- Exposure to data quality, observability, and metadata management tools
- Experience supporting analytics, reporting, or AI/ML workloads
- Experience working on regulatory controls
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