Abhinav Mandal

Data Engineer with hands-on experience building production-style data pipelines, lakehouse architectures, and analytics solutions across financial, geospatial, and geoscience domains using Databricks, Apache Spark, dbt, Airflow, and AWS.

Holds Databricks Certified Data Engineer

Associate, dbt Fundamentals, and DataCamp SQL Associate certifications. MS in Information Systems from Pace University (3.5+ GPA, Academic Scholarship). Strong foundation in data modeling, ETL/ELT design, and cloud-native data engineering.

Data Engineer at Shrive Solutions LLC (2025-06 – Present)

Design and build end-to-end data pipelines on Databricks using PySpark, Delta Lake, and Medallion Architecture. Develop and maintain dbt models with automated testing and documentation. Orchestrate batch and real-time data workflows using Apache Airflow and Databricks Auto Loader. Build analytics-ready Gold-layer datasets and Power BI dashboards. Maintain full project codebases on GitHub.

• Design and build end-to-end data pipelines on Databricks using PySpark, Delta Lake, and Medallion Architecture (Bronze/Silver/Gold), processing datasets ranging from thousands to millions of records with data quality enforcement and quarantine patterns.
• Develop and maintain dbt models (staging, intermediate, mart layers) with automated testing, documentation generation, and lineage tracking integrated with Databricks Unity Catalog.
• Orchestrate batch and real-time data workflows using Apache Airflow DAGs and Databricks Auto Loader with PySpark Structured Streaming, implementing watermarking, retry logic, and exactly-once processing guarantees.
• Build analytics-ready Gold-layer datasets and Power BI dashboards for business KPIs including revenue trends, anomaly detection, and geospatial aggregations.
• Maintain full project codebases on GitHub with architecture documentation, README files, and reproducible notebook structures across all pipelines.

Data Science Volunteer at Bright Mind Enrichment & Schooling (2024-08 – 2025-06)

Analyzed socioeconomic and enrollment trends contributing to data-driven organizational decisions. Collaborated with non-technical staff to translate data needs into structured queries and reports.

• Analyzed socioeconomic and enrollment trends, contributing data-driven findings that informed decisions for key organizational initiatives.
• Collaborated with non-technical staff to translate data needs into structured queries and reports, strengthening stakeholder engagement skills.

Master of Science in Information Systems – Pace University (2022-09 – 2024-05)

Bachelor of Engineering in Electronics & Telecommunication – Nagpur University (2018-08 – 2022-06)