David

Senior Data Engineer with 7+ years of experience designing and building scalable data platforms, ETL pipelines, and analytics systems for large-scale web and marketplace products. Strong expertise in Python-based data engineering, distributed data processing, and modern cloud data platforms. Experienced in developing reliable data pipelines using Apache Spark, Airflow, and Kafka to process large volumes of transactional and behavioral data.

Skilled in building data warehouse models and analytics datasets used by product teams, marketing, and business intelligence stakeholders.

Background in backend development using Java and Node.js with additional frontend experience using React for internal analytics dashboards and operational tools.

Senior Data Engineer - DataKind - Brooklyn, NY

(2025-01)

• Designed and implemented scalable ETL pipelines using Python and PySpark to process booking transactions, merchant activity, and customer interaction datasets.
• Built Apache Airflow workflows orchestrating automated ingestion pipelines from PostgreSQL production databases, Kafka event streams, and external marketing platforms.
• Developed Spark-based aggregation pipelines generating marketplace analytics including booking conversion rates, merchant revenue metrics, and customer retention data.
• Implemented Kafka-based event ingestion pipelines capturing real-time application events such as appointment bookings, cancellations, and payment updates.
• Designed Snowflake data warehouse models used by analytics and product teams for reporting and exploratory data analysis.
• Built curated datasets powering internal dashboards for marketplace growth, marketing campaign analysis, and merchant performance tracking.
• Implemented automated data validation and monitoring pipelines ensuring reliability across production data workflows.
• Collaborated with product managers and analysts to define analytics metrics and data models supporting product decision-making.

Data Engineer - Moneyling - Stamford, CT

(2019-03 - 2024-12)

• Developed Python-based data pipelines processing ticket transactions, event metadata, and user engagement events.
• Built Spark aggregation jobs generating analytics metrics including ticket sales trends, event popularity rankings, and revenue performance reports.
• Implemented Apache Airflow DAGs orchestrating daily ETL pipelines processing ticketing system data.
• Designed dimensional data warehouse models supporting business intelligence dashboards and reporting tools.
• Integrated third-party data sources including Stripe payment data, marketing campaign metrics, and partner event feeds.
• Developed backend APIs using Node.js and Express exposing analytics datasets to internal reporting systems.
• Supported development of internal React dashboards used by operations teams to monitor ticket sales and campaign performance.

Software Engineer - Tech Innovators of America - Dublin, CA

(2017-07 - 2019-02)

• Developed backend services using Node.js and REST APIs supporting web-based enterprise applications.
• Built scripts to process application logs and operational data into structured datasets for analytics.
• Designed MySQL database schemas and optimized SQL queries supporting reporting systems.
• Developed internal dashboards using React for operational monitoring and analytics visualization.
• Assisted in building early ETL pipelines used for internal business intelligence reporting.

Bachelor of Science - Computer Science - University of Houston - Downtown (2012-04 - 2017-05)