We are seeking a talented and experienced Data Platform Solutions Architect to join the Data Solutions domain in EMEA. In this hands‑on role, you will design, build, and optimize scalable, cloud‑native data platform architectures leveraging AWS, Snowflake, Airflow/MWAA, dbt, and modern lakehouse patterns. You will collaborate closely with engineering, analytics, and architecture teams to deliver robust data solutions that enable high‑quality, reliable, and governed data across the enterprise.
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