Senior Python Developer with AWS Expertise

Summary

Jessica

Austin, Texas +1-737-***-**** ************@*****.***

•Python Developer with 3+ years of professional experience designing, developing, and deploying high-performance Python applications for enterprise-scale systems, including financial and healthcare domains.Extensive hands-on expertise in developing event-driven services, REST and GraphQL APIs, and large-scale data ingestion pipelines using Python across AWS cloud environments.Strong experience building ingestion, normalization, and workflow components for processing large datasets, ensuring data quality, consistency, and operational reliability.Proficient in AWS serverless architecture including Lambda, DynamoDB, CloudWatch, S3, and Step Functions for automated and scalable solutions.Skilled in Agile and Scrum methodologies, participating in sprint planning, reviews, retrospectives, and ensuring timely delivery of production-ready features.Hands-on experience in API development and integration, including RESTful and GraphQL APIs, with comprehensive validation, authentication, and performance monitoring.

Skills

•Programming & Query Languages: SQL (Advanced Queries, Joins, CTEs, Window Functions), Python (Pandas, NumPy, Scikit-learn), Data Manipulation & Scripting

•Languages: Python, SQL

•Frameworks / Libraries: Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch, Requests, Boto3, Flask

•Cloud / Platforms: AWS (Lambda, DynamoDB, CloudWatch, S3, Step Functions), Azure

•API Development: REST, GraphQL

•Data Pipelines: ETL, ingestion, normalization, validation, workflow automation

•Tools: Git, Jupyter Notebook, VS Code, Jira, MLflow

•Concepts: Event-driven architecture, Agile, Scrum, CI/CD, Production Support, Data Quality, Exception Handling

Experience

Software Engineer – Kroger, USA Jun 2025 – Present

•Designed and implemented large-scale Python-based data ingestion pipelines that automated the extraction, normalization, and transformation of multi-source enterprise datasets, ensuring high throughput and minimal latency across AWS Lambda functions.

•Built and enhanced index product capabilities leveraging Python and cloud-native services, delivering scalable solutions that improved data processing efficiency by automating key workflows and validation checks.

•Developed and deployed RESTful and GraphQL APIs using Python frameworks to enable seamless integration of data services with internal business applications, incorporating robust exception handling and monitoring mechanisms.

•Implemented event-driven services in AWS using Lambda, DynamoDB, and CloudWatch for real- time processing of streaming data, enabling high reliability and error recovery across multiple business-critical workflows.

• Created automated data validation scripts in Python to verify accuracy, consistency, and completeness of large unstructured datasets before ingestion into operational systems.

•Developed Python modules for asynchronous data processing, enabling concurrent handling of multiple workflow tasks while optimizing resource usage and execution time.

Python developer – Adobe, India Oct 2021 – Jul 2023

•Analyzed digital marketing performance data across Adobe Experience Cloud platforms to optimize campaign attribution models, imp roving ROI visibility by 25% for Marketing stakeholders.

•Developed Python-based ingestion and normalization pipelines for large-scale financial datasets including transactions, credit, and account data, ensuring accurate preprocessing for predictive analytics and reporting.

•Implemented scalable Python modules to support index product capabilities, enabling automated processing of financial events and integration with enterprise banking platforms.

•Designed and built REST and GraphQL APIs in Python to expose financial data services to internal applications, incorporating robust exception management and data validation for high compliance standards.

•Developed Python workflows for credit risk scoring, customer segmentation, and loan eligibility prediction, leveraging historical transaction and service utilization data.

•Built automated ETL pipelines in Python to extract, cleanse, and transform banking datasets from SQL Server and Oracle databases, supporting downstream machine learning and analytics pipelines.

•Designed Python modules for event-driven processing using AWS Lambda and DynamoDB to ensure near real-time financial data availability and automated alerting on exceptions.

•Implemented validation frameworks in Python to ensure accuracy and consistency of all financial data used in internal reporting, predictive models, and dashboarding.

•Developed Python scripts for operational monitoring, logging, and incident response of production data workflows, integrating with CloudWatch and internal monitoring tools.

Software Developer –Energizer, India Mar 2020 – Sep 2021

•Evaluated merchant transaction datasets using SQL to identify growth patterns and churn indicators, enabling a 15% improvement in merchant retention strategies for Fintech operations.

•Built automation script using Confidential API and Python Beautiful Soup to scrape data from social network and other websites using Python.

•Exchanged data with SQL database and NoSQL database such as MongoDB Conducted Big Data analytics using Hadoop MapReduce.

•Generated data-driven reports, data visualization using Tableau Designed front end and backend of the application using Python on Django Web Framework.

•Used HTML, CSS, AJAX, JSON designed and developed the user interface of the website. Developed views and templates with Django view controller and template Language to create a user-friendly website interface.

•Used JavaScript and JSON to update a portion of a webpage. Develop consumer-based features using Django, HTML and Test-Driven Development (TDD).

•Developed Python web services for processing JSON and interfacing with the Data layer. Used GIT version control and deployed project to Heroku.

•Increased the speed of pre-existing search indexes through Django ORM optimizations. Used standard Python modules e.g. CSV, Robot parser, Iter tools, Pickle, Jinja2, Xml for development.

•Managed, developed, and designed a dashboard control panel for customers and Administrators using Django, HTML, CSS, JavaScript, Bootstrap, JQuery and RESTAPI calls. Query and set up employee registration and login using Python PostgreSQL

•We use a multiple row data storage strategy called MVCC to make effective PostgreSQL responsive in Querying and storing in database.

Education

Master Of Sciences: Advanced Data Analytics

University of North Texas, Denton Texas

May 2025

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