Data Modeling Engineer RRS & Migration

Click Global Talent; Kuala Lumpur; Remote; MYR 180,000 - 240,000; Full time

Job summary

Click Global Talent is seeking a Data Modeling Engineer with expert knowledge of Regulatory Reporting System (RRS) data and migration strategies. The role spans analysis, design, build, SIT, UAT, and go-live with ongoing reconciliation and cutover responsibilities.

You will collaborate with business analysts, ETL/ELT developers, DBAs, and the data architect. The ideal candidate has extensive experience in enterprise data warehouses, dimensional modeling, and complex migrations across platforms,

Qualifications

• Minimum 8 years in data modelling / data engineering.
• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline.
• Deep data modelling across conceptual, logical, and physical layers using dimensional, 3NF, and Data Vault techniques.
• Proven delivery of a platform migration with schema/DDL conversion and data-type translation.
• Experience with migration where structures and results must be preserved exactly.

Responsibilities

• Produce and maintain data models for staging, integration, and consumption layers.
• Apply dimensional, 3NF, and Data Vault techniques and define grain, keys, relationships, and history.
• Convert legacy RRS data models to the target platform with correct lineage and auditability.
• Design physical models for the target MPP engine and advise ELT developers on model structures.
• Create Source-to-Target Mapping specifications and maintain data lineage and metadata.
• Lead end-to-end delivery lifecycle: design, build, SIT, UAT, parallel run, cutover.

Skills

Data modelling

Data engineering

SQL

Data Vault

ETL/ELT

Data warehouse

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or related

Tools

GaussDB/DWS

Netezza

Teradata

Snowflake

DDL

Job description

Click Global Talent is recruiting a Data Modeling Engineer with expertise in Regulatory Reporting System (RRS) and data migration for a leading organisation. This is a full-time, program-based, multi-year remote engagement. The role involves a phased delivery approach, from analysis and design through build, SIT, UAT, parallel run, and go-live, with the engineer engaged throughout the entire lifecycle, including reconciliation and cutover. You will work closely with business analysts, ETL/ELT developers, DBAs, and the data architect.

Key responsibilities

Produce and maintain conceptual, logical, and physical data models for staging, integration, and consumption layers. Apply dimensional, 3NF, and Data Vault techniques, defining grain, keys, relationships, history, and naming standards. Review and govern models for consistency, reusability, and conformance to target architecture.

Convert legacy RRS data models to the target platform, preserving regulatory calculations and reporting outputs. Enhance existing RRS models for new platform or regulatory requirements without breaking existing submissions. Build new RRS models for reporting requirements not met by the legacy estate, ensuring support for BNM / PIDM regulatory submissions with correct lineage and auditability.

Perform 1:1 conversion of legacy objects (tables, views, structures) into the target DWS, translating Netezza data types, DDL, and constraints to GaussDB/DWS equivalents. Preserve structure, grain, and output exactly for like-for-like migrations, documenting any unavoidable deviations. Define and specify schema-conversion rules and reusable patterns.

Design physical models for the target MPP engine, including distribution/hash keys, partitioning, compression, and storage layout for optimal query and batch performance. Advise ELT developers on set-based, push-down-friendly model structures.

Produce Source-to-Target Mapping (STTM) specifications with transformation, derivation, and data-type conversion rules. Maintain data lineage and metadata for models in governance/catalogue tooling.

Define model-level reconciliation and validation rules (row counts, control totals, balances) between legacy and target, and support SIT, UAT, and parallel-run reconciliation. Investigate and resolve model-related defects and mismatches to root cause.

Work closely with business analysts, ETL/ELT developers, DBAs, and the data architect, translating requirements and BRDs into buildable models. Maintain modelling standards, a data dictionary, and model documentation.

About you

Minimum 8 years in data modelling / data engineering, with substantial time on enterprise data warehouse and data-migration programmes.

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline.

Deep, hands-on data modelling across conceptual, logical, and physical layers, using dimensional, 3NF, and Data Vault techniques.

Proven delivery of a platform migration - ideally MPP-to-MPP (e.g., Netezza, Teradata → GaussDB/DWS, Snowflake) - including schema/DDL conversion and data-type translation.

Experience with point-to-point / functional-equivalence (like-for-like) migration where structures and results must be preserved exactly.

Strong, practical SQL and DDL; able to write and validate DDL, profile data, and build reconciliation queries against large datasets independently.

Experience producing source-to-target mappings that engineering can build from without rework.

Experience across the full delivery lifecycle: design, build, SIT, UAT, parallel run, and cutover.

Banking / financial-services background; excellent written and spoken English (Bahasa Malaysia an advantage).

Mandarin-speaking candidates only.