Data Platform Solution Architect New

Key Responsibilities:

• Design and architect end-to-end cloud data platform solutions across AWS, Snowflake, Airflow, dbt, and lakehouse components.
• Analyse system requirements and develop enterprise data models aligned with business needs and scalable architecture principles.
• Define and oversee the implementation of data integration architectures, including ingestion pipelines, data flows, orchestration, and ELT/ETL processes.
• Build, optimize, and maintain high-performance data pipelines for ingestion, transformation, storage, and delivery across warehouse and lakehouse layers.
• Apply hands-on tuning and optimization to Snowflake, S3-based lakehouse structures (Iceberg), Airflow DAGs, and dbt transformation models.
• Ensure data governance, lineage, quality, observability, access control, and compliance throughout the entire data lifecycle.
• Evaluate, recommend, and implement emerging data technologies and architectural improvements to enhance platform scalability and performance.
• Monitor and troubleshoot data workflows, compute layers, storage layers, and orchestration to ensure platform reliability.
• Produce high-quality Architecture Design Documents (ADDs), solution designs, and technical standards aligned with enterprise architecture principles.
• Collaborate with engineering teams to maintain platform reliability through automation, observability, and continuous improvement.
• Provide production support, guiding teams through root-cause analysis, pipeline recovery, and optimization strategies.
• Champion best practices in data engineering, lakehouse design, ELT architecture, CI/CD, and cloud-native patterns.

Technical Qualifications:

• Minimum 7 years’ experience in a similar position within a dynamic and fast paced environment at enterprise production scale.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• Strong Proficiency in SQL, Data Integration (IBM Streamsets, Informatica) and Data Transformation (Airflow + DBT) with thorough understanding of data transformation processes.
• Strong Experience in AWS (IAM, Lambda, EKS, S3 (Datalake), EMR (Pyspark), Datalakehouse (Iceberg), MWAA and other services relevant to data architecture and analytics
• Expertise in Snowflake, with a proven ability to optimize queries for efficient data retrieval.
• Experience with both batch (StreamSets) and streaming (Kafka) data solutions.
• Familiarity with data modelling concepts (Inmon, Kimball, Data Vault, etc.).
• Exposure to CI/CD or Infrastructure-as-code (Terraform or any other) is a plus.
• Experience with Application Performance Monitoring Frameworks.
• Knowledge of data quality and security best practices is advantageous.
• Proven experience in producing sound and comprehensive Architecture Design Documents and ability to align with Enterprise Architecture Principles.
• Understanding of the classic software architecture patterns.

Non-Technical Skills:

• Strong attention to detail, with a proactive approach to identifying and resolving problems.
• A genuine interest in emerging data technologies and a curiosity about continuous improvements
• Excellent verbal and written communication skills.
• Attention to detail mindset, proactively identify problems & evaluate solutions
• AI Empowered Experience