Platform ownership
From VPC and IAM foundations through CDC, warehouse modeling, and analytics delivery.
Experience
Experience across platform engineering, cloud infrastructure, and analytics delivery.
Hands-on work across AWS, GCP, streaming systems, warehousing, infrastructure, and stakeholder-facing analytics, with consistent depth in platform design and execution.
Platform ownershipCloud infrastructureAnalytics delivery
Track record
Where the work has depth.
Real-time systems
Streaming and operational analytics work with Kafka, Kinesis, Databricks, and quality controls.
Analytics products
Natural-language analytics flows, APIs, charts, and stakeholder-facing outputs built on trusted data.
Cloud translation
AWS production work paired with a deliberate GCP build that carries the same enterprise standards into a second cloud.
Timeline
Selected roles and delivery history.
2025 — Present
Independent Data and Platform Engineer
Architecting production data platforms across AWS and GCP with a focus on lakehouse design, networking foundations, environment discipline, and analytics systems that teams can trust and use every day.
Consulting Practice · Berlin, Germany
- Architected an AWS medallion lakehouse platform: PostgreSQL via DMS CDC into Bronze, Silver, and Gold S3 layers, Glue PySpark transformations, dbt on Athena, and Redshift Serverless with Spectrum.
- Provisioned the platform through modular Terraform across Dev, Staging, and Prod, covering VPC networking, IAM, storage, orchestration, and CI/CD through GitHub Actions.
- Built a natural-language analytics agent on curated platform data using FastAPI, Streamlit, ECS Fargate, and Claude, with SQL guardrails, session flow, charts, and reporting.
AWSGCPTerraformNetworkingKafkadbtFastAPI
2022 — 2024
Data Engineer · Digital Spine GmbH
Built a real-time IoT data platform serving operational analytics, with strong attention to latency, reproducibility, and data quality before production ingestion.
Digital Spine GmbH · Berlin, Germany
- Built a real-time IoT data platform using Databricks Asset Bundles and Amazon Kinesis, processing over one million elevator telemetry records daily with sub-minute latency.
- Established GitHub Actions CI/CD for Databricks and dbt, ensuring consistent and reproducible deployments across all environments.
- Enforced data quality using PySpark and dbt with unit tests, integration tests, and quarantine handling before bad records reached production consumers.
- Built Power BI dashboards and communicated pipeline findings clearly to engineering, operations, and business stakeholders.
DatabricksKinesisPySparkPower BIGitHub Actions
2020 — 2022
Data Specialist · Potters Real Estate Limited
Moved a real estate analytics workflow from manual reporting toward more reliable, centralized, and decision-ready data pipelines.
Potters Real Estate Limited · Nigeria
- Built ELT workflows using dbt and AWS to centralize and standardize real estate data, replacing manual processes with automated pipelines.
- Analyzed platform and marketing data to surface property demand trends, informing acquisition and marketing strategy.
- Deployed Power BI dashboards that contributed to stronger lead generation and better decision support.
dbtS3RedshiftPower BI
Core stack
Technologies used across production work.
The tools matter, but the more important signal is the kind of ownership they were used to support.