Senior Data Engineer Data & AI Platform Modernization

Modernizing cloud data platforms for analytics and AI.

I build scalable, reliable, governed data foundations across Databricks, Snowflake, AWS, Azure, and GCP.

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Professional delivery

Selected experience.

Cloud modernization, analytics engineering, streaming, and operational delivery across five client environments.

CAVA

  • Consolidated Amazon S3, Redshift, POS, workforce, and ERP data into Databricks and Delta Lake, reducing processing time by 30% and laying the foundation for planned AI-driven personalization.
  • Optimized compute and processing workloads, reducing platform costs by 20% and query-execution time by 25%.
  • Scaled data integration and reporting during expansion from 341 to 398 restaurants.

Freddie Mac

  • Designed and implemented a metadata-driven PySpark pipeline on AWS EMR for mortgage loan-evaluation workloads.
  • Decomposed ULAD loan-evaluation documents into 8 staging datasets, orchestrated through AWS Step Functions with DynamoDB-backed configuration.
  • Published 18 analytics-ready datasets to AWS Glue and Snowflake for research and enterprise reporting.

Lexia Learning

  • Built pipelines and marts for Cambium's Customer Data 360 initiative to unify district, school, and educator data across Lexia and Voyager Sopris Learning.
  • Migrated most Tableau reports from direct MySQL connections to Amazon Redshift, reducing report-processing time by 70%.

Calix

  • Migrated 250 TB of historical Oracle data to Azure Blob Storage using Azure Data Factory and a self-hosted integration runtime.
  • Implemented dbt tests across 8 business-critical models, maintaining 99.9% data integrity.
  • Bridged on-premises Kafka with Azure Event Hubs, reducing network-issue response time by 18% across 3 data products.

American Express

  • Transformed customer signals into risk attributes for new-account and proactive credit-line eligibility workflows.
  • Automated the Proactive credit-line pipeline from ODL feature derivation through eligibility, decisioning, fulfillment, and Cornerstone publication, processing 25 TB daily.
  • Built and supported validation, fulfillment, and audit workflows for credit-line offers across Japan and Europe.

Technical focus

Data engineering for analytics and AI.

With 9+ years across finance, retail, telecom, and EdTech, I modernize enterprise data systems into governed, reliable platforms for analytics and AI applications.

My work spans cloud migrations, lakehouse architectures, batch and streaming pipelines, observability, and cost optimization.

Core engineering

Python, SQL, PySpark, Scala, dbt, Delta Lake, Iceberg, Kafka, Airflow, and data modeling.

Cloud data platforms

Databricks and Snowflake; AWS: EMR, Glue, Redshift, and Step Functions; Azure: ADF, ADLS Gen2, and Event Hubs; GCP: BigQuery and GCS.

AI & data operations

Amazon Bedrock, Strands Agents, LangChain, RAG, LLM-powered observability, data quality, and CI/CD.

Credentials

Certifications & training.

Azure Data Engineer Associate

Microsoft credential

Data Analytics – Specialty

AWS credential

dbt Fundamentals

dbt Labs training

Gen AI Fundamentals

Databricks Academy training

Contact

Let's talk data engineering.

Recruiting for a Senior Data Engineer role? Email me or connect with me on LinkedIn.

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