Andrew Norris

Experienced Senior Data Engineer with 9+ years of expertise designing and scaling cloud-native data platforms across AdTech and Healthcare domains. Skilled in building robust ETL/ELT pipelines, orchestrating workflows with Airflow and dbt, and optimizing analytics infrastructure using Databricks, Snowflake, and Delta Lake. Proven ability to deliver real-time data solutions, implement Medallion lakehouse architectures, and drive data reliability through governance frameworks such as Great Expectations.

Known for bridging engineering with business outcomes, mentoring teams, and enabling faster, data-driven decision-making through high-quality, scalable data systems.

Senior Data Engineer at Optum (2020-06 – Present)

• Led the development of a large-scale OptumRx pharmacy data platform, using Kafka, AWS Glue, and Redshift, processing 25B+ monthly prescription, claims, and operational events to power real-time analytics, system monitoring, and enterprise reporting.
• Architected the "Support360 Insight Engine," enabling predictive insights on support and operational data, reducing critical incidents by 20% across enterprise healthcare systems.
• Replatformed legacy ETL pipelines to dbt + Airflow, reducing data latency from 12 hours to under 1 hour for real-time operational dashboards supporting clinical and support teams.
• Designed and implemented a Medallion lakehouse architecture using Databricks + Delta Lake, improving ML feature engineering for healthcare use cases and reducing compute costs by 35%.
• Created HIPAA-compliant CI/CD pipelines for dbt models and Spark jobs using Terraform and GitLab CI, reducing release errors by 65% and ensuring secure, auditable deployments for PHI data workflows.
• Built a cost-to-serve analytics pipeline using Snowflake and dbt, integrating usage, support, and billing data to identify $5M+ in recoverable costs and guide service tier optimization.
• Partnered with BI analysts to build healthcare marketing attribution models using Snowflake data marts and star schema design, influencing $15M+ in patient acquisition and engagement outcomes.
• Implemented data quality and observability frameworks using Great Expectations, achieving 99%+ precision in anomaly detection and schema validation across critical healthcare pipelines.
• Led cross-cloud data sync architecture (AWS to Azure) using S3, Event Hub, and Kafka Connect, ensuring global failover readiness and compliance with multi-region SLAs.
• Delivered an internal "DataOps Toolkit" using Prometheus and Grafana to monitor pipeline SLAs, latency, and failure rates in real-time.
• Mentored 6+ data engineers, driving adoption of scalable data architecture, healthcare data governance best practices, and high-quality engineering standards.

Data Engineer at Facebook (2017-06 – 2020-06)

• Built and maintained large-scale data pipelines for the Instagram Ads Platform, processing 5B+ user interaction events daily to power ad delivery, analytics, and reporting systems.
• Developed scalable ETL/ELT workflows using Python, SQL, Apache Spark, Hive, and Presto, supporting analytics and ML feature pipelines across 100+ TB of daily data.
• Designed and optimized data models (fact/dimension schemas) to enable real-time campaign performance tracking, improving advertiser reporting latency by 30%+.
• Partnered with ML engineers to deliver high-quality datasets for ad ranking, targeting, and personalization, contributing to measurable improvements in engagement and conversion metrics.
• Improved pipeline performance and reliability by optimizing distributed Spark jobs and query execution, reducing data processing latency by ~40% and increasing SLA adherence to 99.9%+.
• Implemented data validation and quality checks using internal frameworks, reducing data inconsistencies and downstream reporting issues by 25%+.
• Collaborated with cross-functional teams (product, analytics, infra) to support A/B testing and experimentation pipelines, accelerating data-driven decision-making for ads optimization.

Bachelor's Degree in Computer Science – University of Toronto (2013 – 2017)