AWS Data Engineer (Data Modelling, Financial Sector with …, Bunghmun

A US/Canadian based IT MNC is hiring AWS Data Engineer/ Data Modeller for one of its Banking Client. Mandatory Skills: AWS Data Engineering, Data Modelling, Glue, Airflow, Kafka, Experience working with BIAN (Banking Industry Architecture Network) Framework Location: Remote Time Overlap: Till 11 PM IST Experience in Data Engineering, for a customer data repository project. Responsible for modeling data aligned with the BIAN architecture, translating business requirements and ensuring integration with CRM. Essential knowledge in AWS technologies: Aurora PostgreSQL, S3 Lakehouse (Iceberg), Glue, Debezium CDC, MSK. Advanced English is essential. We value experience in the financial sector and familiarity with BIAN. Focus on data quality and collaboration with engineering is expected for efficient pipelines. Required skill: 1. Lakehouse Data Modeling on Amazon S3 o Design Medallion architecture (Bronze/Silver/Gold) o Model data for scalability, partitioning, and domain-based access o Handle schema evolution and time-travel use cases 2. AWS Glue + PySpark (ETL Modeling) o Translate logical/physical models into PySpark transformations o Optimize joins, partition pruning, pushdown predicates o Manage schema via Glue Data Catalog 3. Schema Design & Metadata Management o Define canonical schemas and data contracts o Maintain centralized metadata using Glue Catalog o Versioning and backward compatibility of schemas 4. Contemporary Table Formats (Apache Iceberg / Delta) o Implement ACID-compliant tables on S3 o Design for incremental loads, CDC, and snapshot-based querying o Optimize compaction and partition strategies 5. Streaming & CDC Data Modeling (Kafka / MSK) o Design event schemas aligned with domain models o Model change data capture flows into lakehouse o Ensure consistency between streaming and batch layers 6. Advanced Data Modeling Techniques o Data Vault 2.0 (Hubs, Links, Satellites) o Dimensional modeling (Star/Snowflake) o SCD (Type 1/2/3), surrogate keys, historization 7. Data Governance & Quality Engineering o Data lineage, cataloging, metadata-driven pipelines o Data quality frameworks (Great Expectations, Deequ) o RBAC, audit, compliance 8. Lakehouse & Medallion Architecture o Bronze (raw CDC), Silver (conformed), Gold (business-ready) o Schema evolution, late arriving data, deduplication 9. Orchestration & Pipeline Engineering o Apache Airflow (DAG design, dependency mgmt, SLA handling) o Hybrid orchestration (event + schedule driven) o CI/CD for data pipelines 10.Canonical & Contract-First Data Design o Canonical schemas, data contracts, schema versioning o API/event schema alignment (Avro/JSON/Protobuf) 11. Domain-Centric Data Modeling o Nice to have experience BIAN-aligned service domains () o Domain-driven design with clear data ownership and boundaries Apply on Kit Job: kitjob.in/job/4lknkk