Senior Data Modelling Engineer - SAP to AWS Migration (Supply Chain)

Where:

Business Hours:

Process:

1. ICS 1st Interview (30 minutes)

2. CV shared with client, followed by 1-2 further rounds

Context of work:

• The client is a global energy company undergoing a significant transformation to support the energy transition. We work within their Customers & Products (C&P) division, serving both B2C and B2B customers across key markets such as the UK, US, Germany, Spain, and Poland.
• This business unit includes mobility (fuel and EV), convenience retail, and loyalty.

Required Skills and Experience:

• Proven experience in data modelling and data pipeline development.
• Proficiency with tools like ER Studio, STTM, AWS Glue, Redshift & Athena, and Power BI.
• Strong SQL and experience with generating DDL scripts.
• Experience working in SAP data environments.
• Experience in any of these domain areas is highly desirable: Logistics, Supply Planning, Exports and IFOT.
• Familiarity with cloud platforms, particularly AWS.
• Hands-on experience with DevOps and Agile methodologies (e.g., Azure ADO).
• Strong communication and documentation skills.
• Ability to work collaboratively with cross-functional teams.

Key Responsibilities

Data Modelling

• Initiate and manage Gap Analysis and Source-to-Target Mapping Exercises.
• Gain a comprehensive understanding of the EA extract.
• Map the SAP source used in EA extracts to the AWS Transform Zone, AWS Conform Zone, and AWS Enrich Zone.
• Develop a matrix view of all Excel/Tableau reports to identify any missing fields or tables from SAP in the Transform Zone.
• Engage with SME’s to finalise the Data Model (DM).
• Obtain email confirmation and approval for the finalised DM.
• Perform data modelling using ER Studio and STTM.
• Generate DDL scripts for data engineers to facilitate implementation.

Data Engineering

• Set up infrastructure for pipelines – this includes Glue Jobs, crawlers, scheduling, step functions, etc.
• Build, deploy, test and run pipelines on demand in lower environments.
• Verify data integrity: no duplicates, all columns in final table etc.
• Write unit tests for methods used in the pipeline and use standard tools for testing.
• Code formatting and linting.
• Collaborate with other Modelling Engineers to align on the correct approach.
• Update existing pipelines for CZ tables (e.g., Serverless Data Lake Framework (SDLF)) where necessary with new columns if they are required for EZ tables.
• Raise DDP requests to register databases and tables, and to load data into the raw zone.

Other

• Create comprehensive good documentation. Ensure each task is accompanied by detailed notes specific to its functional area for clear tracking and reference.
• Analyse and manage bugs and change requests raised by business/SMEs.
• Collaborate with Data Analysts and Virtual Engineers (VE) to refine and enhance semantic modelling in Power BI.
• Plan out work using Microsoft Azure, ADO. Dependencies, status and effort are correctly reflected.