About Our Client Partner

Our client is a leading, diversified conglomerate with major operations spanning in diverse industries. The organization is undergoing a significant digital and AI transformation, establishing a robust data foundation to power enterprise-wide decision-making and next-generation analytics. This role sits within a centralized Group function, responsible for designing and building the scalable, cloud-native data platforms that connect business data to strategic insights.

Role Summary

We are seeking an experienced Data Engineers to lead the design, construction, and optimization of the Group's enterprise data platform and ETL/ELT pipelines. This pivotal role will define the technical architecture for the movement and storage of data, ensuring it is readily available, governed, and performant for consumption by the Group AI & Advanced Analytics team and various business applications. The Architect will bridge the gap between business requirements and scalable cloud infrastructure.

Key Responsibilities

Data Architecture and Platform Design
- Design and implement the Group-wide, cloud-native data architecture (e.g., Data Lake, Data Warehouse, Data Mesh principles) to support analytics, reporting, and Machine Learning workloads.
- Define technical standards and best practices for data storage, security, quality, and governance across all data assets.
- Select and evaluate technologies for the data stack, ensuring compatibility with major cloud platforms (e.g., Azure/AWS/GCP).
Data Pipeline Development (ETL/ELT)
- Build, manage, and optimize scalable ETL/ELT pipelines to ingest data from diverse source systems (e.g., SAP ERP, CRM, operational databases) into the centralized data platform.
- Implement robust data quality checks, monitoring, and error handling within data pipelines.
- Utilize modern data processing frameworks (e.g., Spark, Databricks) and orchestration tools (e.g., Airflow) for automation and efficiency.
Solution Architecture and Integration
- Act as the technical Solution Architect for analytics projects, translating data science models (from the AI team) and business requirements into concrete data flow designs and production-ready deployments.
- Ensure seamless integration between the core data platform and consumption layers, including BI tools (Power BI), internal APIs, and front-end applications.
- Partner with IT and Security teams to ensure all data solutions meet enterprise-level security and compliance standards.
Mentorship and Documentation
- Provide technical leadership and mentorship to junior data engineers, fostering skills in cloud data services and modern data modeling techniques.
- Develop and maintain comprehensive technical documentation, including data dictionaries, platform diagrams, and ETL/ELT process flows.

Requirements

Experience: Typically 5-8 years of experience in Data Engineering, Data Architecture, or a related role, with proven experience designing and deploying end-to-end data solutions in a cloud environment.
Technical Expertise:
- Programming: Advanced proficiency in SQL and Python is mandatory.
- Cloud: Hands-on experience designing and operating services in at least one major cloud platform (Azure preferred, AWS, or GCP), specifically involving data services (e.g., Azure Data Factory, Azure Synapse, S3/Redshift).
- Data Modeling: Strong expertise in relational and non-relational database design and modern data modeling techniques (e.g., dimensional modeling, Data Vault).
Systems Knowledge: Familiarity with enterprise systems, particularly SAP ERP data structures, is highly desirable.
Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related quantitative field.
Attributes: Strong analytical and problem-solving skills, excellent communication abilities to clearly articulate technical designs to both technical and business stakeholders.

Senior Data Engineer/Architect