Vetted Data & Analytics Professionals

Zhiwen Zhao

Screened

Junior Data Engineer specializing in cloud ETL and big data platforms

New York, NY3y exp

“Data engineer focused on transit/transportation datasets, building Spark-based pipelines that ingest from Oracle/APIs, apply PySpark data-quality fixes, and publish star-schema fact tables to Azure Data Lake. Experienced troubleshooting complex Spark failures (using checkpointing to manage long lineage) and operating Airflow-driven backfills and GitLab CI deployments for production DAGs.”

Caillou Borden

Screened

Intern-level Sales and Outreach Professional specializing in sustainability and client engagement

New York, NY1y exp

“Sales/business development candidate with hands-on outbound experience across donor/partner and community stakeholder outreach, including multi-channel campaigns (email, word-of-mouth, door-to-door) managed through Salesforce. Applied data-driven targeting (NY census) to focus outreach on high-poverty areas and has experience operating in an early-stage/ambiguous environment at NBC during the Paris Olympics, using proactive coordination and meetings to create structure.”

“Analytics professional with experience across retail and healthcare, including Kroger and CVS Health. They have built SQL and Python workflows to clean and operationalize messy data, and have owned patient adherence/retention analytics projects that informed targeted interventions and improved refill and retention reporting.”

“Analytics engineer/data analyst with Bank of America experience turning fragmented financial data across SQL Server, PostgreSQL, Kafka, and flat files into trusted Snowflake/dbt reporting models. Stands out for unifying disputed business definitions like churn and payment success rate, automating manual analysis in Python, and pairing strong data quality rigor with stakeholder adoption through self-service dashboards.”

“Data/ML engineer with end-to-end ownership experience at Charles Schwab, spanning data ingestion, anomaly detection, data quality infrastructure, and dashboards used daily by compliance and business teams. Stands out for debugging complex cross-layer issues in systems processing 17M+ records per day and for turning one-off data quality checks into reusable frameworks that scaled across business units.”

“Frontend engineer with JPMorgan experience shipping internal dashboards and real-time trading data interfaces. Stands out for a disciplined AI-assisted development workflow: uses AI selectively for boilerplate, rigorously reviews outputs against actual schemas and architecture, and has hands-on experience with React, GraphQL, WebSockets, Redux, and direct model API integrations.”