Akash Ranganathan

About

Data Engineer with a track record of building scalable data pipelines, dashboards, and data workflows that empower data-driven decision-making across healthcare, SaaS, and life sciences. Experienced in Databricks, PySpark, Tableau, and Power BI; adept at collaboration between data engineering and analytics teams, and delivering end-to-end data solutions from ingestion to governance.

Experience

• Data Engineer · Apollo Trident Inc.10-01-2025 –

  Designed and optimized scalable data pipelines using Databricks (Spark SQL, PySpark) to process large volumes of structured and semi-structured data, improving data reliability and enabling data-driven decisions. Developed Tableau dashboards and semantic data models for automated self-service reporting. Built and operationalized end-to-end data workflows in Dataiku, including data ingestion, data preparation, feature engineering, and pipeline automation. Enabled collaboration between data engineering and analytics teams.

• Data Analyst Intern · Autism Strong Foundation05-01-2025 – 07-31-2025

  Led migration of 500k+ patient and program records across CRM systems. Built automated data cleaning and normalization workflows leveraging Python and ETL scripting. Audited 12+ SaaS applications for patient management. Developed Tableau and Power BI dashboards for patient outcomes and operations. Performed population health and geospatial analytics to identify high-impact regions.

• Business Analyst Intern · Unilever, Mumbai, India04-01-2023 – 07-31-2023

  Conducted UX and workflow analysis of the B2B app Shikhar, reviewing 50K+ merchant interactions, identifying bottlenecks, and recommending process improvements to reduce operational errors. Analyzed shopper ordering patterns using SQL and Excel, generating insights on platform adoption and transaction behavior. Defined and monitored KPIs for order completion, efficiency, and user satisfaction, enabling data-driven decisions that improved order success rates by 18%. Developed dashboards and recommendations to optimize self-ordering workflows for retailers.

• Associate · Cognizant Technology Solutions08-01-2021 – 07-31-2024

  Led Quality Analysis for QuickBooks and Model N by validating tickets across 15 modules, identifying high-severity defects, driving prioritization with engineering teams, and reducing average defect resolution time from 3 days to 1 day. Partnered with developers and product managers to analyze recurring defects, implementing preventive QA workflows. Orchestrated test planning, execution, and defect management for 10+ critical releases, standardizing processes to improve sprint delivery speed by 15%. Developed real-time defect dashboards using Power BI, consolidating data from multiple sources to enable faster root-cause analysis.

• Data Analyst Intern · Tata Consultancy Services, Hyderabad, India07-01-2020 – 10-31-2020

  Performed data extraction, transformation, and loading (ETL) using Azure Data Factory v2 and SQL Server, migrating healthcare and operational datasets to Azure SQL Database and Data Lake Gen2. Designed and automated data validation and integrity checks to verify record accuracy, schema alignment, and completeness during migration. Collaborated with a leading pharma enterprise to support a major Azure Cloud Transformation initiative, focusing on data migration and modernization of legacy on-prem systems.

Education

• University of North Carolina, Charlotte, NCMaster of Science, Information Technology (Analytics)
• Rajalakshmi Engineering College, Chennai, IndiaBachelor of Engineering, Computer Science

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