Data Lake Solution Architect

Job Summary

We are looking for an experienced Data Lake Solution Architect to design, develop, and maintain scalable data lake solutions, with SAP S/4HANA as the primary source system. The candidate will be responsible for defining the data architecture, designing data ingestion and transformation pipelines, ensuring data quality, and overseeing ongoing support and enhancement activities.

Key Responsibilities

• Design and implement end-to-end data lake architecture for enterprise data platforms.
• Integrate data from SAP S/4HANA into the data lake using appropriate extraction, replication, and ingestion mechanisms.
• Define data ingestion, transformation, storage, and processing strategies for structured and semi-structured data.
• Design scalable and efficient ETL/ELT pipelines to support business reporting and analytics.
• Lead data lake development, production support, troubleshooting, and enhancement activities.
• Ensure data quality, consistency, security, governance, and performance optimization.
• Collaborate with SAP functional teams, data engineers, business stakeholders, and analytics teams.
• Establish best practices for data modelling, metadata management, monitoring, and data lifecycle management.
• Identify performance bottlenecks and implement improvements to data pipelines and storage.
• Prepare technical architecture documents, design specifications, and implementation guidelines.
• Provide technical leadership, code reviews, and guidance to data engineering team members.

Required Skills and Qualifications

• 8+ years of experience in data engineering, data architecture, or data lake solutions.
• Strong experience in designing and implementing enterprise-level data lake architectures.
• Hands-on experience integrating SAP S/4HANA data with data lake platforms.
• Strong understanding of SAP data extraction methods, APIs, OData, CDS Views, and other relevant integration mechanisms.
• Experience with ETL/ELT tools, data pipelines, and distributed data processing.
• Proficiency in SQL and data modelling concepts.
• Experience with cloud-based data platforms such as AWS, Microsoft Azure, or Google Cloud is desirable.
• Knowledge of data governance, security, metadata management, and data quality frameworks.
• Experience in production support, root cause analysis, performance tuning, and solution enhancement.
• Strong problem-solving, communication, and stakeholder management skills.

Work Location: Remote