Shrasti Tomar
Data Engineer | Analytics Expert | Python, Java, C++ | Azure | ETL | SQL & NoSQL | Spark SQL | Visualization | Pyspark | AWS Lambda | Athena | Airflow | Firebase | Meta Graph API | Google Ads API
- Role
- Data Engineer at Zupee
- Location
- Ghaziabad, UP, IN
- LinkedIn followers
- 500 followers
About Shrasti Tomar
Hey there! I am Shrasti Tomar, passionate Data Engineer and Analytics professional with a strong command of Python, Java, and C++. Proficient in leveraging Azure Data Factory, Synapse, and Databricks for seamless ETL pipelines. Skilled in working with SQL, MongoDB, and Azure SQL, along with expertise in Spark, PySpark, and essential libraries like NumPy and Pandas. Adept at crafting compelling visualizations using Tableau and Power BI.
Experience
Data Engineer
Nov 2023 — Present · Gurugram, IN
Led end-to-end development of marketing data pipelines across Meta, Google Ads, AppsFlyer, and CleverTap—automating campaign performance tracking and attribution for 6+ apps; reduced manual reporting time by 80%- Built scalable ETL frameworks using Airflow, PySpark, and Athena, processing over 50M+ user events monthly, enabling daily campaign reporting and increasing marketing data availability SLAs from ~70% to >98%- Automated Meta remarketing and suppression cohorts (e.g, APK signups, FTD users) using the Meta Graph API, improving audience freshness and driving 10–15% uplift in CTR across targeted campaigns- Deployed hourly spend tracking and live dashboards for Meta and Google campaigns, giving marketing teams real-time visibility into spends, installs, and ROI—leading to a ~25% improvement in budget pacing- Implemented alerting and validation for partner event jobs, identifying discrepancies and reducing undetected failures by >90%; added threshold-based sanity checks across 100+ daily job executions- Migrated 20+ ad-hoc marketing upload jobs into a unified, modular framework with structured error handling and observability—resulting in zero post-deployment issues since go-live- Automated Tableau dashboard refreshes via Airflow and Tableau APIs, introducing retry logic and failure notifications—cutting refresh failure rates from ~30% to under 5%- Enabled state-level campaign cost visibility by ingesting granular data from Meta and Google APIs; initiated partner integration with Liftoff and Moloco to cover 100% of performance marketing spend centrally.
Education
Lovely Professional University
BTech - Bachelor of Technology
2018 — 2022
Lovely Professional University
Master of Business Administration - MBA
2022 — 2024
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