Data Engineer – AWS & Snowflake

Hadoop Migration | Banking Modernisation ProgramWe are seeking an experienced Data Engineer to support a major banking data modernisation program, migrating existing Hadoop data workloads and pipelines to AWS and Snowflake.
This is a hands-on engineering role focused on building reliable data pipelines, transforming and migrating complex datasets, and delivering secure, scalable and production-ready data solutions within a highly regulated banking environment.
What You’ll DoAnalyse existing Hadoop datasets, pipelines, transformations, dependencies and workload characteristics.Build and migrate batch, incremental and near-real-time data pipelines into AWS and Snowflake.Develop ingestion, transformation and integration solutions across raw/landing, curated and business-consumption layers.Re-engineer Hadoop-based workloads into scalable cloud-native data solutions.Develop Snowflake databases, schemas, tables, views, stages, Snowpipe, Streams and Tasks.Implement ETL/ELT pipelines and enterprise data models supporting analytics and reporting.Perform data profiling, cleansing, validation, reconciliation and migration testing.Implement data quality, lineage, metadata and governance requirements.Apply security controls including IAM/RBAC, encryption, masking, privacy and audit logging.Optimise Snowflake queries, warehouse sizing, workload performance and consumption costs.Build automated CI/CD and DataOps deployment processes.Implement monitoring, alerting, logging and operational-support capabilities.Produce technical designs, data mappings, pipeline documentation and operational runbooks.Work closely with data architects, AWS and Snowflake specialists, security teams, analysts and managed-service teams.
What You’ll BringStrong hands-on data engineering experience with Snowflake and AWS.Experience migrating Hadoop-based data platforms, datasets and pipelines to cloud environments.Strong Snowflake development skills across databases, schemas, warehouses, tables, views, stages, Snowpipe, Streams and Tasks.Strong experience building batch, incremental and near-real-time ingestion pipelines.Advanced SQL skills and experience with Python, PySpark or similar data engineering technologies.Strong knowledge of ETL/ELT, data integration, data warehousing and lake/lakehouse concepts.Experience with dimensional and relational modelling, curated data products and semantic layers.Experience with AWS data ingestion, storage, processing and integration services.Knowledge of Hadoop technologies such as HDFS, Hive, Spark and related ecosystem tools.Experience with data quality, reconciliation, metadata, lineage, cataloguing and governance.Knowledge of IAM/RBAC, encryption, masking, privacy controls and secure data engineering.Experience with Git, CI/CD, DataOps and automated testing and deployment.Strong Snowflake performance optimisation and cloud cost-management skills.Experience delivering production monitoring, observability, operational readiness and support documentation.Banking, financial services or highly regulated enterprise experience is strongly preferred.Snowflake and AWS data engineering certifications are highly regarded.Experience with Power BI consumption patterns, enterprise semantic models or data-governance platforms would be advantageous.
Why Apply?This is an opportunity to contribute to a significant Hadoop-to-AWS-and-Snowflake transformation, solve complex data engineering challenges and help build a modern enterprise data platform within a major banking environment.
If you are a hands-on Data Engineer with strong Snowflake, AWS and data migration experience, we would welcome your application.