I am a Lead Consultant and Staff Data Engineer / Data Architect with over 11 years of experience designing, building, and optimizing large-scale data platforms across Databricks, Apache Spark, AWS, Azure, and GCP. I currently work at Xebia on a global marketplace platform (Adevinta / Marktplaats). Previously, I worked as a Staff Data Engineer at Altimetrik, supporting Takeda Healthcare, and spent over 7 years at Hughes Systique. My experience spans enterprise data platforms, Lakehouse architecture, ETL/ELT pipelines, real-time streaming, CDC, data engineering system design, cloud migrations, performance optimization, and data architecture. I help Data Engineers learn faster, avoid unnecessary trial and error, and prepare confidently for their next career move. Areas I can help with: Data Engineering Roadmap I help build a practical, structured roadmap covering Python, SQL, PySpark, Spark, Data Structures and Algorithms, Data Modeling, Data Warehousing, ETL/ELT, Data Pipelines, Databricks, Delta Lake, AWS, Azure, GCP, Kafka, Streaming, Airflow, dbt, Snowflake, System Design, and Data Architecture. The goal is to learn the right things in the right order for your specific career target. Data Engineering System Design Many experienced engineers struggle to translate technical knowledge into real-world architecture. I help with Data Lake and Lakehouse architecture, batch and streaming architecture, CDC and event-driven systems, Databricks and Delta Lake architecture, Kafka and streaming systems, ETL/ELT architecture, data warehousing, scalability and reliability, performance and cost optimization, cloud data architecture, and real-world design problems. Senior Data Engineering Interview Preparation For those preparing for Senior, Staff, Lead, or Data Architect roles, I help identify gaps, build a preparation strategy, and practice problems across SQL, Python, PySpark, DSA, Data Modeling, Big Data, Cloud, Databricks, System Design, Architecture, and scenario-based questions. Mock Interviews and Interview Preparation Practical, realistic mock interview sessions covering SQL and Python coding, PySpark and Spark, data engineering fundamentals, data modeling, cloud, Databricks, system design, architecture discussions, troubleshooting scenarios, and senior-level behavioral and technical discussions. Career Growth Guidance Support for professionals moving from Data Engineer to Senior Data Engineer to Lead or Staff Engineer to Data Architect, including identifying gaps in your current profile and building a practical plan to close them. Real-World Data Engineering Projects Guidance on designing projects using Databricks, Spark, Delta Lake, AWS/Azure/GCP, Airflow, dbt, Kafka, CDC, Data Warehousing, and Lakehouse architecture, with a focus on demonstrating real engineering skills rather than tutorial-based implementations. Resources and Learning Strategy Help identifying the most relevant resources and building a structured learning path, so you spend more time learning and building and less time searching. Selected experience: Optimized a 10 PB incremental Databricks/dbt model and eliminated full-table scans on a 28.4 TB daily mart. Redesigned Airflow ingestion to run workloads in parallel, reducing pipeline runtime from approximately 31 hours to 14 minutes. Optimized Spark/DLT workloads processing over 2 million healthcare records daily, achieving approximately 40 percent faster processing. Led a team of 14 Data Engineers across enterprise data engineering initiatives. This mentorship is suited for anyone starting their Data Engineering journey, preparing for their first Data Engineer role, moving from Data Engineer to Senior Data Engineer, preparing for Staff, Lead, or Architect roles, preparing for Databricks interviews, working through Data Engineering System Design, planning a cloud or data platform migration, or seeking guidance on career direction or resume review. Feel free to book a session to discuss your goals.