Aakash Jadhav

About Aakash Jadhav

I am a Data Analyst with 4+ years of experience delivering data-driven solutions across healthcare, finance, and enterprise domains. I specialize in transforming complex datasets into actionable insights, building scalable data pipelines, and improving data quality to support business decision-making. In my current role, I work extensively with SQL, Python, and AWS to manage healthcare datasets, automate reporting workflows, and ensure high data integrity across systems. I’ve built ETL pipelines, developed validation frameworks, and created dashboards that enable stakeholders to make faster, more accurate decisions. Previously, I worked on large-scale datasets across multiple industries, where I designed dashboards, performed statistical analysis, and implemented data validation and reconciliation frameworks. My work has consistently focused on improving operational efficiency, reducing manual effort, and enhancing reporting accuracy. Core expertise includes: • SQL (advanced queries, optimization, data validation) • Python (Pandas, NumPy, data analysis & automation) • ETL pipelines & data engineering workflows • AWS (S3, Glue, Athena, Lambda) & Snowflake • Data visualization (Power BI, Tableau) • Data quality, reconciliation & governance • Exploratory data analysis, A/B testing, and forecasting I am particularly interested in roles that combine data analytics and engineering where I can work on data pipelines, cloud platforms, and scalable analytics solutions. Currently open to Data Analyst / Data Engineer opportunities (W2/Full-time) in the US. Portfolio: github.com/aakashjjadhav a••••••••@gmail.com

Experience

1. Data Analyst

   CitiusTech

   Mar 2025 — Present · NY, US

   Maintained and validated healthcare databases using SQL, Python, and AWS Glue, performing data verification and reconciliation toensure accuracy, compliance, and integrity across reporting systems.• Generated and distributed recurring healthcare reports using SQL, Python, and Power BI, enabling data-driven decision-makingand improving reporting efficiency for clinical, operational, and administrative stakeholders.• Managed provider and system data updates using SQL and AWS services, ensuring accurate database records, seamless integration,and alignment with regulatory reporting and compliance requirements.• Developed automated data validation and reconciliation workflows using Python, SQL, and AWS Glue, reducing data discrepancies,improving backlog resolution, and enhancing overall data quality and system reliability.• Collaborated with IT, clinical, and administrative teams using JIRA and Agile tools, acting as a liaison to resolve data issues,streamline workflows, and improve system performance.• Led process improvement initiatives by building automated reporting pipelines using AWS, SQL, and Python, reducing manualeffort, increasing operational efficiency, and strengthening data governance and compliance standards.

Education

• Universal College of Engineering

  Bachelor of Engineering - BE, Electronics Engineering

• Pace University - Seidenberg School of Computer Science and Information Systems

  Master's degree, Information Science/Studies