Data Engineer | Data Analyst | Data Warehouse | ETL | Cloud Data Platform
I've spent the past 9+ years turning messy data into something teams can actually rely on — from ETL/ELT pipelines and data warehouses to streaming systems and cloud platforms. These days I'm also exploring how AI/LLMs fit into that world, building data-driven solutions on top of it.
| Layer | Tech Stack |
|---|---|
| Orchestration | Apache Airflow, Dagster, Prefect, Apache NiFi |
| Language | Python, SQL |
| Processing | Apache Spark, Apache Flink |
| Streaming | Apache Kafka |
| Ingestion | Airbyte, Debezium, Talend, Pentaho, IBM DataStage, SSIS |
| Cloud Computing | AWS, GCP, Azure, Alibaba Cloud |
| Lakehouse | Apache Iceberg, Amazon S3, Google Cloud Storage, SeaweedFS |
| Data Platform | Databricks, Microsoft Fabric, Snowflake |
| Transformation | dbt, SQLMesh |
| Warehouse and Query | BigQuery, Redshift, ClickHouse, DuckDB, PostgreSQL, SQL Server, Oracle, Trino |
| Search and Enrichment | OpenSearch, MongoDB |
| Monitoring | Grafana, Prometheus |
| BI and Visualization | Power BI, Tableau, IBM Cognos, Metabase, Plotly Dash, Superset |
| DevOps and Containerization | Docker, Podman |
| Collaboration | Jira, Confluence |
| AI/LLM Data Processing | LLM-driven data workflows |
- Data Engineering and Data Analysis
- Data Warehousing with Data Vault 2.0 and Kimball methodology
- ETL and data pipeline development
- Business Intelligence and dashboard development
- SQL development across PostgreSQL, Oracle, MySQL, SQL Server, BigQuery, Redshift
- Workflow orchestration with Apache Airflow
- Streaming and integration with Kafka and Apache NiFi
- Cloud data solutions on Google Cloud Platform, AWS, and Alibaba Cloud
- Data platforms including Databricks, Microsoft Fabric, and Snowflake
- LinkedIn: linkedin.com/in/juliuschaesar-dev
- Email: [email protected]