Annie Mo

Staff Data Engineer with 10+ years of experience delivering scalable data platforms and cloud-native infrastructure across healthcare, finance, and AI-driven environments. Expert in ETL/ELT pipelines, data warehousing, and orchestration using Python, SQL, Snowflake, BigQuery, Airflow, and dbt across AWS, GCP, and Azure. Proven in modernizing legacy systems, improving data quality and observability, and optimizing performance at scale.

Collaborative leader focused on building resilient data solutions that drive analytics, machine learning, and business impact.

Staff Data Engineer - Corrohealth

(2024-05)

• Architected and scaled a cloud-native data platform for an AI-driven coaching product, delivering end-to-end data capabilities across ingestion, transformation, warehousing, and analytics.
• Built and optimized large-scale data pipelines and Snowflake-based data models to support real-time analytics, machine learning, and product intelligence.
• Established robust orchestration, data quality, and observability frameworks to ensure reliability, scalability, and operational efficiency.
• Partnered with cross-functional stakeholders to translate business needs into high-impact data products and KPIs, enabling data-driven decision-making.
• Led data platform best practices, mentoring engineers and driving improvements in performance, cost efficiency, and data governance.

Lead Data Engineer - Cummins

(2021-02 - 2023-12)

• Designed and maintained scalable ETL/ELT pipelines ingesting retail transactions, customer behavior, and inventory data into cloud data warehouses to support analytics and operational reporting.
• Developed Python and SQL-based transformation workflows to cleanse, standardize, and integrate multi-source datasets, improving reporting accuracy and downstream reliability.
• Built and optimized dimensional data models to enable merchandising analytics, demand forecasting, pricing optimization, and customer segmentation.
• Implemented workflow orchestration using Airflow to automate batch processing, manage dependencies, and enhance pipeline stability and recovery.
• Leveraged cloud platforms and distributed processing frameworks to process large-scale retail datasets while optimizing performance and infrastructure costs.
• Partnered with analysts, product teams, and business stakeholders to translate reporting requirements into scalable data products and analytics-ready datasets.
• Introduced data quality checks, monitoring, and alerting mechanisms, reducing data discrepancies and improving trust in executive dashboards.
• Supported CI/CD and version-controlled development practices, improving deployment reliability, documentation, and cross-team collaboration.

Senior Data Engineer - Dataforest

(2018-12 - 2020-09)

• Architected and delivered secure, scalable healthcare data platforms integrating clinical, claims, and operational datasets for analytics and regulatory reporting.
• Built and optimized ETL frameworks to standardize sensitive healthcare data, enabling advanced analytics, care optimization, and compliance.
• Designed domain-specific data models supporting population health, utilization analysis, and patient outcomes measurement.
• Established governance, security, and access control practices aligned with HIPAA, ensuring trusted and compliant data ecosystems.
• Partnered with data science and analytics teams to enable predictive modeling and data-driven decision-making.
• Drove performance optimization across data platforms, improving efficiency, reliability, and reporting speed.
• Mentored engineers and led best practices in scalable data engineering within a highly regulated healthcare environment.

Data Engineer - CHI Software

(2016-01 - 2018-09)

• Built foundational data pipelines and models supporting financial analytics, including transactions, revenue tracking, and fraud detection.
• Developed scalable ETL frameworks using Python and SQL to integrate and reconcile complex financial datasets.
• Designed data models enabling reporting, auditing, and operational insights across finance functions.
• Automated data processing workflows, improving reliability and operational efficiency.
• Collaborated with business stakeholders to deliver actionable data products and dashboards.
• Established data quality and monitoring practices to ensure trusted and production-ready data systems.

Bachelor of Computer Science - Computer Science