Lucas Demitroff Brandi

Data & Analytics Engineer

I build scalable data pipelines and analytics infrastructure. My work focuses on transforming raw data into actionable insights through reliable ETL systems, data warehousing, and real-time processing solutions.

Currently focused on building data platforms that enable data-driven decision making. I specialize in Python, SQL, Apache Spark, and cloud data services including AWS and GCP.

Skills

Languages

  • Python
  • SQL
  • Scala
  • Bash

Data Processing

  • Apache Spark
  • Apache Kafka
  • Apache Airflow
  • dbt

Databases

  • PostgreSQL
  • BigQuery
  • Snowflake
  • MongoDB
  • Redis

Cloud & Tools

  • AWS
  • GCP
  • Docker
  • Kubernetes
  • Terraform

Experience

2023 — Present

Senior Data Engineer · Company Name

Lead the development of real-time data pipelines processing millions of events daily. Architected and implemented a modern data lakehouse solution using Delta Lake and Apache Spark, reducing query latency by 70%.

PythonSparkAirflowAWSDelta Lake
2021 — 2023

Data Engineer · Previous Company

Built and maintained ETL pipelines for analytics and machine learning teams. Designed data models and implemented data quality monitoring systems across multiple data sources.

PythondbtBigQueryKafkaKubernetes
2019 — 2021

Junior Data Engineer · First Company

Developed automated data ingestion workflows and reporting dashboards. Collaborated with data analysts to optimize SQL queries and improve data accessibility.

SQLPythonPostgreSQLAirflowTableau

Projects

Real-Time Analytics Pipeline

Built a streaming data pipeline that processes 1M+ events per minute using Apache Kafka and Spark Structured Streaming. Includes real-time dashboards and alerting.

Apache KafkaSparkPythonInfluxDBGrafana

Data Quality Framework

Open-source data quality monitoring framework with automated anomaly detection, data profiling, and Slack notifications for data pipeline failures.

PythonGreat ExpectationsAirflowPostgreSQL

ETL Orchestration Platform

Centralized platform for managing and monitoring data workflows across multiple teams. Features include dependency visualization, cost tracking, and SLA monitoring.

AirflowFastAPIReactDockerTerraform

Contact

I'm always interested in discussing data engineering challenges, new opportunities, or potential collaborations.

Get in Touch
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