15+ years of enterprise data platform leadership. Architecting scalable AWS/GCP Medallion Lakehouses (Apache Iceberg, dbt), high-throughput PySpark pipelines, geospatial analytics, and automated data governance.
From initial cloud data architecture blueprinting to hands-on execution and team mentoring.
Architecting robust, scalable Medallion data lakehouses (Bronze/Silver/Gold) supporting Analytics, Machine Learning, and GenAI feature store requirements with strict schema evolution.
Seamless migration from legacy Hadoop/Cloudera or Snowflake setups to native AWS/GCP cloud platforms. Refactoring ETL pipelines to cut infrastructure costs by up to 40%.
High-throughput processing of spatial datasets, vector geometries, and point clouds. Building distributed spatial indexing and sub-second GIS analytics queries.
Implementing AWS Lake Formation, Unity Catalog, and automated compliance enforcement agents (GDPR, Antitrust, PII masking, fine-grained access control).
Custom PySpark / Scala pipeline engineering, star-schema data volume reduction algorithms (extracting low-cardinality keys, surrogate integer mapping, Parquet compression).
Interim technical leadership, business information domain modeling, engineering best practices, CI/CD pipeline automation, and upskilling in-house data teams.
Inspect real implementation patterns, schema optimizations, and benchmarks used in enterprise consulting engagements.
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Designed and delivered an Apache Iceberg-based AWS lakehouse platform with granular RBAC governance and dbt semantic modeling.
Re-engineered legacy on-prem Hadoop workflows to native AWS Glue & EMR services with automated Infrastructure as Code.
Refactored heavy analytics queries and migrated workloads to native AWS Glue and Athena processing layers.
Built automated compliance enforcement agent on Delta Lake to guarantee GDPR compliance and automated data masking across domains.
Built reusable IaC product for analytics, ML, and GenAI feature engineering with embedded data quality frameworks.
Designed and built a fully open-source, self-hosted data platform running on Kubernetes (K3s) with Spark, Apache Polaris, Marimo, and Vault.
Battle-tested enterprise technologies utilized across architecture engagements.
Explore how enterprise data flows through the modern medallion architecture, semantic layers, processing compute engines, and downstream GenAI and BI applications. Hover over any node to trace lineage.
Flexible consulting structures tailored to your data architecture maturity and team goals.
Rapid assessment of your existing cloud infrastructure, ETL bottlenecks, and cost drivers with actionable architectural recommendations.
Production-ready Medallion Lakehouse MVP built on AWS/GCP with Apache Iceberg, dbt semantic layers, and Infrastructure as Code.
Embedded senior technical leadership guiding your data team through complex migrations, domain modeling, and high-scale scaling challenges.
Simulate the estimated timeline, expected ROI, and recommended engagement for your organization.
With over 15 years of hands-on data engineering experience, I specialize in transforming complex, siloed data environments into clean, high-throughput, AI-ready data platforms.
My career spans lead engineering roles at major enterprise organizations including Deutsche Bahn (DB InfraGo, DB Fernverkehr AG), Telekom Deutschland GmbH, and Zalando SE. I advocate for clean code, infrastructure as code, automated compliance, and open table formats like Apache Iceberg.
Book an initial technical consultation to discuss your data architecture requirements, cloud migrations, or lakehouse initiatives.
✉️ Send Email to timor@timor-dataworks.com