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Strong Tier-1 brand, popular data-engineer title, mid-level experience, and broad cloud/pipeline skills drive high competition.
Core data engineering skills transfer broadly, but finance and portfolio context increases industry-specific fit sensitivity.
Explicit 5+ years, required Snowflake/cloud, Python/SQL, and leadership make filters highly strict.
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Lead the design, development, and optimisation of scalable data pipelines and platforms for structured and unstructured data supporting analytics and AI use cases.
Own end-to-end data engineering solutions including ingestion, transformation, orchestration, storage, and serving layers to ensure reliability, scalability, and maintainability.
Provide technical leadership by mentoring junior engineers, driving architectural decisions, and collaborating with cross-functional teams to deliver enterprise-scale data products.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
5+ years of relevant experience in data engineering.
Strong expertise in Python, SQL, cloud data platforms (e.g., Snowflake), and modern data pipeline/orchestration frameworks.
Experience with data modelling, ETL/ELT design, pipeline optimisation, data quality controls, monitoring, and CI/CD practices.
Experienced in architecting and delivering complex, production-grade data engineering solutions in cloud environments.
Demonstrates technical leadership with strong architectural thinking and ability to mentor teams through complex data initiatives.
Skilled at collaborating with AI engineers, product managers, and business stakeholders to translate requirements into robust data solutions.