Data Engineer

● Worked with clients to understand their business use cases, provided strategic recommendations on data structures and delivery formats, and
implemented solutions that improved data usability and decision-making efficiency.
● Participated in sales and pre-sales calls to present data solutions, answer technical queries, and demonstrate business value—contributing to
securing $500K+ in new business contracts.
● Collaborated with finance and infrastructure teams to analyze operational costs across data platforms (GCP , Snowflake, Databricks).
Recommended and headed cost optimization projects that reduced operational costs by $50K+ and accelerated processing efficiency by 20%.
● Processed millions of rows using SQL on BigQuery, Snowflake, and Databricks to create actionable insights for high-frequency trading and risk
assessment. Reduced manual reporting efforts by 30% through automated data aggregation.
● Led a team of 10+ to resolve production issues, achieving an 80% reduction in backlog and improving data delivery timelines by 50% through
workflow monitoring using JIRA dashboards.
● Designed a versioned data tracking system in Snowflake, reducing discrepancy errors by 20% and increasing data reliability for financial reporting.
● Programmed Python scripts to transform complex data (XML/XBRL, JSON) into structured models, reducing processing time by 40% and improving reporting accuracy.
● Constructed and optimized 50K+ data pipelines using Airflow, GCP , decreasing data delivery failures by 15% through automated error handling.
● Established data quality rules, improving data accuracy by 25% and reducing reprocessing time.
● Spearheaded migration to new deployment engines, automating data processing and enhancing accuracy by 15%.
● Produced real-time insights to trading teams, identifying and resolving data anomalies that led to $500K+ savings in trading errors annually.

● Evaluated 1M+ mortgage loans using Statistical Models, uncovering fraudulent activity and improving fraud detection accuracy by 20%.
● Wrote and maintained 5K+ lines of SQL code to extract and analyze key data points, enabling real-time decision-making and reducing report
generation time by 90%.
● Built Excel dashboards with PIVOT tables and Macros to visualize loan timelines, reducing loan research time from 2 hours to 10 minutes.
● Presented to business stakeholders, guiding them on KPIs to monitor when analyzing loans. Increased dashboard adoption by 40% and enabled
customer service reps to address customer pain points 30% faster by using data-driven insights.
● Applied ML and NLP to analyze loan data, increasing accuracy in keyword classification by 80%, which enhanced early fraud detection.