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About

Alex Huggler

I am a senior data and analytics engineer with six years at AT&T, building production data platforms on Azure and Databricks. My work spans PySpark ingestion, dbt analytics models, BI delivery, and the operational side of running pipelines that finance and operations teams depend on.

I am happiest when a hard, ambiguous business problem gets translated into a clear data model and a reliable pipeline. Recent work includes fraud-signal detection that drove ~$900K/yr in loss reduction and analytics ownership of a $2.2B portfolio. I am currently focused on streaming and lakehouse patterns, applied AI for data tooling, and senior-level remote roles.

I write code that is boring on purpose - well-tested, instrumented, easy for the next engineer to understand. I treat documentation, runbooks, and data contracts as part of the deliverable, not a nice-to-have.

Stack proficiency

Area Tools Level
Compute PySpark, Apache Spark Structured Streaming, Databricks Expert
Cloud Azure (ADF, ADLS Gen2, Synapse), AWS (S3, Glue, Athena) Advanced
Lakehouse Delta Lake, Apache Iceberg, Parquet Advanced
Warehouse Snowflake, Synapse Dedicated SQL Advanced
Modeling dbt, SQL, dimensional modeling Expert
Orchestration Apache Airflow, ADF, Databricks Workflows Advanced
Streaming Apache Kafka, Spark Structured Streaming Advanced
Languages Python, SQL, Bash, a little Scala Expert
Infra Terraform, Docker, GitHub Actions Working
ML / AI Azure ML, Anthropic API, prompt engineering for data tooling Working

Certifications

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