Description
We are seeking a Data Engineer-VP to lead the design, development, and modernization of enterprise data platforms, focusing on Ab Initio, Hadoop ecosystem, and AWS cloud technologies.
The successful candidate will be responsible for building scalable data solutions, driving migration of on-premise data processing workloads to AWS, defining target-state architecture and migration roadmaps, and ensuring secure, reliable, and high-quality data delivery.
Key responsibilities:
- Build and maintain data architectures, pipelines, data warehouses, and data lakes to ensure accurate, accessible, and secure data
- Design and implement data warehouses and data lakes that manage data volumes and velocity, adhering to security measures
- Develop processing and analysis algorithms for complex data
- Collaborate with data scientists to build and deploy machine learning models
- Contribute to strategy, drive requirements, and make recommendations for change
- Manage and mitigate risks, demonstrating leadership and accountability
- Demonstrate comprehensive understanding of the organisation's functions to contribute to business goals
Requirements:
- Strong Ab Initio development expertise (GDE, EME, Conduct>It, Continuous Flows, Metadata Hub)
- Experience with Hadoop ecosystem technologies (Hive, Spark, HDFS, Impala, Oozie, Sqoop, Kafka)
- Knowledge of AWS Cloud Data Services (Glue, EMR, Athena, S3, Lambda, Redshift, Iceberg)
- DevOps & CI/CD experience (GitLab, Jenkins, Infrastructure as Code, automated deployments)
- Stakeholder & Delivery Leadership experience
Preferred skills:
- Python, SQL, and Spark for large-scale data engineering and automation
- Data Architecture, Data Governance, Data Quality, and Metadata Management
- AI & Advanced Analytics (Machine Learning, Generative AI, Prompt Engineering)
- Financial Services & Risk Domain Knowledge (Credit Risk, Basel, IFRS9, Regulatory Reporting, Data Controls)