Naga Samyukta B. — Business Development Executive

With over 9 years of experience in the data ecosystem, I specialize in the intersection of Data Engineering and Advanced Analytics. I don’t just build pipelines; I architect scalable data systems that turn raw complexity into clear, high-impact business outcomes. My approach combines the rigor of software engineering with a deep passion for finding the "so what?" behind every dataset. My expertise lies in building robust ETL/ELT pipelines and reusable data models using SQL, Python, Spark, and dbt. I thrive on the challenge of curating data at scale, transforming messy, distributed sources into unified "single-source-of-truth" layers that power both automated business metrics and machine learning models. Highlights of my technical impact: Engineering for Efficiency: Engineered automated data models and workflows using Alteryx, Spark, and SQL, reducing manual processing effort by 36% and accelerating time-to-insight for strategic cost analysis. Scalable Architecture: Integrated disparate data sources into a cohesive Data Lake, leveraging cloud platforms (Snowflake, AWS, GCP) to ensure high availability and data trust. GenAI & Innovation: Architected backend infrastructure for GenAI and LLM applications, including RAG pipelines that extract actionable insights from unstructured content. Operational Excellence: Automated end-to-end reporting pipelines using Tableau and Python, providing real-time visibility into KPI trends for executive leadership. Beyond the code, I am a strategic partner who translates ambiguous business questions into technical specifications. Whether it’s optimizing healthcare journeys or navigating compliance-heavy (PHI/HIPAA) environments, I ensure every system I build is accurate, auditable, and performant. I am passionate about pushing the boundaries of data infrastructure in the Life Sciences, Healthcare, and Technology sectors. Core Technical Arsenal: Languages: Python, SQL, Spark, R. Infrastructure: Informatica, dbt, Airflow, Databricks, Kafka, Snowflake, AWS, GCP, Azure. Focus Areas: Data Modeling, ETL/ELT, GenAI/LLM Pipelines, Data Quality & Governance. Worked on achieving a single-layer data warehouse by integrating data from multiple source applications using a Data Lake. Strong exposure to Data Profiling and possesses knowledge of Data migration, Data Quality, Data analytics. Google Data Analytics certified. Widespread industry understanding in the Life Sciences and Health Care (LSHC) AHM250 professional certification in the US HealthCare Insurance Domain Certified Azure Data Engineer Associate.

Stackforce AI infers this person is a Data Engineering and Analytics expert in the Healthcare and Technology sectors.

Location: Boston, MA, United States

Experience: 8 yrs 4 mos

Skills

Data Engineering
Etl/elt
Data Visualization
Data Analysis

Career Highlights

Engineered automated data models reducing manual effort by 36%.
Architected scalable data systems for high-impact business outcomes.
Expert in building robust ETL/ELT pipelines and data models.

Work Experience

Inspire

Senior Data Analyst (4 yrs)

Senior Data Analyst - Data Management and Infrastructure (8 mos)

BeiGene

Advanced Analytics Intern (10 mos)

University of Utah

Graduate Teaching Assistant (4 mos)

Deloitte Consulting

Data Analyst - Dell (1 yr 6 mos)

Business Technical Analyst - Anthem (2 yrs 10 mos)

Education

Master's of Science - MS at University of Utah - David Eccles School of Business

Bachelor's degree at G Narayanamma Institute of Technology and Sciences

at KESHAVA REDDY TALENT SCHOOL,KURNOOL,AP

Naga Samyukta B.

Business Development Executive

Boston, MA, United States8 yrs 4 mos experience

Highly StableAI Enabled

Key Highlights

Engineered automated data models reducing manual effort by 36%.
Architected scalable data systems for high-impact business outcomes.
Expert in building robust ETL/ELT pipelines and data models.

Stackforce AI infers this person is a Data Engineering and Analytics expert in the Healthcare and Technology sectors.

Contact

Skills

Core Skills

Data EngineeringEtl/eltData VisualizationData Analysis

Other Skills

Data WarehousingStatistical Data AnalysisSQLPythonData ModelingETLAlteryxSparkHealth care IndustryStrategic PlanningTableauData Visualization (Tableau, Power BI, Looker)Cloud Computing (AWS, Azure, GCP)KafkaStreamSets

About

Experience

8 yrs 4 mos

Total Experience

4 yrs 4 mos

Average Tenure

4 yrs

Current Experience

Inspire

2 roles

Senior Data Analyst

May 2022 – Present · 4 yrs · United States

Proactively identified and evaluated opportunities for operational efficiency in cost analysis, leading to the development of robust data models that reduced manual processes by 36%.
Leveraged script lifting techniques with advanced data mining methodologies to extract usable insights from unstructured patient-generated content, producing reports comparing drug effectiveness within online communities against national benchmarks.
Built a Virtual registry data mart using SQL for data collection, data ops, and patient, caregiver engagement procedures for distributed registries and managed day-to-day registry operations.
Spearheaded the design and deployment of a virtual registry across diverse sources, surveys, PRO to generate a comprehensive data mart.
Identified areas for improvement in annual quality measure reporting by analyzing healthcare claims data; developed and implemented AI-supporting SQL solutions that reduced manual data validation by 15%.
Collaborated with stakeholders to understand business requirements and proactively identified opportunities to automate data integration, designing ETL pipelines that unified diverse data sources for exploratory analysis.
Partnered with the marketing team to define key performance metrics and design A/B tests on email campaigns and landing pages, using Google BigQuery and Excel to analyze results.
Analyzed business workflows to identify inefficiencies in reporting, then translated findings into an actionable recommendation to automate processes, delivering timely insights to leaders.
Built ETL pipelines to ingest Google Analytics transactional data into Snowflake.
Successfully delivered high-quality Real-World Evidence analysis using unsupervised learning and data mining, extracting actionable insights from complex datasets.
Performed comprehensive data cleaning and profiling of claims and EHR data using Databricks and R, laying the foundation for an Integrated Member Data Authentication product.

Data WarehousingStatistical Data AnalysisSQLPythonData ModelingETL+2

Senior Data Analyst - Data Management and Infrastructure

May 2022 – Jan 2023 · 8 mos · United States

Developed data models using the ETL process to enable analysis of member medical history, procedure costs, and condition costs using claims data.
Developed interactive Tableau dashboards with KPI indicators, leveraging Python and SQL, to track page speed metrics, enabling business leaders to identify performance trends and optimize member experience.
Generated metrics using Python, enabling a deeper understanding of user retention, engagement, churn, and conversion rates, leading to data-driven insights and actionable recommendations.
Collaborated with the team to address client inquiries by utilizing the developed data models, including vital signs, treatments, laboratory tests, and results. Provided actionable insights to improve member products and businesses.

Health care IndustryStrategic PlanningPythonSQLTableauData Engineering+1

Beigene

Advanced Analytics Intern

Jun 2021 – Apr 2022 · 10 mos · San Mateo, California, United States

Implemented operationalizing analytics and submitted reports in on-demand analytics platform using SQL and Tableau
Integrated secondary research findings with other analytical insights (primary research, forecasting) within the Commercial Operations and Business Analytics (COBA) team using Altreyx.
Designed and developed ETL data pipelines using Alteryx from a wide variety of data sources and performed transformations as per the user requirement and performed explanatory data analysis using Python.
Automated new patient stats report for the supply and demand that generates the usage of SD and SP on weekly, monthly, and quarterly and visualized quarterly business review (QBR) metrics using Tableau.
Performed descriptive analysis using A/B testing on Promotion effectiveness and plotted the results using the R ggplot2 package.
Experience in working with business analysts to identify, study, and understand business requirements and translate them into ETL code in the Requirement Analysis phase.

Data Visualization (Tableau, Power BI, Looker)Cloud Computing (AWS, Azure, GCP)Data VisualizationData Engineering

University of utah

Graduate Teaching Assistant

Jan 2021 – May 2021 · 4 mos · Salt lake city,Utah, United States

Teaching assistantship for CS 5530 - Database Systems. Database System covers the topics on applying data modeling concepts such as the relational model and entity-relation model to identify and reason about the data needs of a problem (including entity and referential integrity) and design a database solution to the problem. Design a database and related queries and integrate them into a full software system using a high-level programming language to solve a complex data-driven problem, database performance criteria, including the effect of index choice and query formulation, identify where explicit transactions and isolation levels are needed, and show an understanding of transaction processing in an RDBMS

Deloitte consulting

2 roles

Data Analyst - Dell

Jun 2019 – Dec 2020 · 1 yr 6 mos

The main objective of the project was to achieve a single-layer data warehouse Dell Data Lake connecting to connection to 30+ sources with data of suppliers, items, products, facilities, and related transactions. We worked on building an enterprise-wide real-time streaming architecture with technologies like Kafka, stream sets. We then build use-case-specific dashboards with actionable insights for the business users. It helps them in forecasting the demand and maintain the right inventory by ensuing Parts supply to facilities
Developed Stream set transformations and Jobs for extracting the real-time streaming data from RabbitMQ, Kafka using parallel jobs with various operational sources like SQL Server, Oracle, Flat files.
Developed a standardized approach to analyze and report supplier's data under a single roof by reducing the manual work of days to merely a few hours.
Integrated the Data for clients to view by developing the models and derive insights using the MDM platform for forecasting the demand and supply. Master data management (MDM) holds the key to improving performance and reducing cost in every area of business operation-from customer account management and product development to marketing, manufacturing, supply chain optimization, and more.
Created RDL views for consumer systems on top of the landing zone normalized tables and transformed layers using the relational model.
Extensively used Continuous Integration – Continuous Delivery (CI-CD) framework for deploying the code.
Participated in Requirement Gathering, Business Analysis, User meetings, discussing the issues to be resolved, and translating user inputs into ETL mapping documents.

Data Visualization (Tableau, Power BI, Looker)Cloud Computing (AWS, Azure, GCP)Data EngineeringData Visualization

Business Technical Analyst - Anthem

Aug 2016 – Jun 2019 · 2 yrs 10 mos

Worked for one of the largest health Insurance Plan providers in the US which has a wide range of Health Insurance Packages to suit the customer’s needs. The purpose of the project is to generate extracts as per the vendor use-case that includes member, med, and RX claims, and provider details of the health plans that customers enroll for. These extracts are generated from the Enterprise Data warehouse data which is sourced from various source systems.
Analyzed, transformed, and loaded data using data-warehousing techniques and helped the providers maximize their data mining capabilities, and made clinical data handling a lot easier.
Built models to tokenize the PHI data and ensure that these models are responsible for providing personal health information (PHI) data is masked and protected.
Extensively used advanced SQL analytic functions.
Analyzed policy changes on member enrollment and made statistical inferences for management decisions.
Developed the scheduled Control-M jobs using predictive analysis and simulation to transfer data through the model from source to target systems that facilitate daily, a weekly, monthly load of data.
Built models that detect job failures helped businesses predict and minimize the run failures and have the data available as per the schedule.

Data Visualization (Tableau, Power BI, Looker)Cloud Computing (AWS, Azure, GCP)Data EngineeringData Analysis