Senior Python Developer for Financial Services

Swathi A

Senior Python Developer Flask · Pandas · NumPy · Financial Applications

Mobile: 312-***-**** Email: ************@*****.***

PROFESSIONAL SUMMARY

•Senior Python Developer with 11+ years of experience building backend services, data pipelines, and web applications, including financial services platforms at Capital One supporting transaction processing, reconciliation, and reporting.

•Deep hands-on expertise in Python, Flask, FastAPI, and Django, with strong numerical and analytical data skills in Pandas and NumPy for large-scale data transformation, aggregation, trend and variance analysis.

•Front-end experience with JavaScript and TypeScript, delivering Flask-based internal web tools that let business and finance users search data, review exceptions, and download reports.

•Proven record of refactoring and modernizing legacy code into modular, well-tested services, reducing technical debt while improving maintainability, performance, and scalability.

•Experienced supporting business-critical batch and reporting runs: monitoring execution, troubleshooting failures, performing root-cause analysis, and validating the integrity, accuracy, and timeliness of outputs through automated reconciliation.

•Writes clean, production-grade code backed by automated unit, integration, and contract tests (PyTest, unittest) with strong coverage, and enforces quality through code reviews and mentoring.

•Profiles and tunes Python and SQL workloads (vectorized Pandas/NumPy operations, batching, concurrency, caching, indexing) to improve runtime efficiency for high-volume processing.

•Delivers end-to-end solutions across data, services, APIs, and infrastructure, coordinating with data engineers, platform teams, security, and business stakeholders including finance, risk, and analysts.

•Supports infrastructure upgrades, cloud migrations, and new technology adoption using Docker, Kubernetes, AWS, Terraform, and CI/CD (GitHub Actions, Jenkins), with secure-by-default practices.

•Microsoft Certified Azure AI developer, with a strong interest in applying LLMs and agentic workflows to improve analyst productivity and forecasting operations.

•Contributes actively to design discussions, documentation, and runbooks; communicates technical tradeoffs clearly to engineers and non-technical stakeholders.

TECHNICAL SKILLS

•Languages: Python, SQL, PL/SQL, JavaScript, TypeScript, Bash

•Python Web & Services: Flask, FastAPI, Django, Django REST Framework, Pydantic, SQLAlchemy, Celery

•Data & Numerical Computing: Pandas, NumPy, PySpark, Apache Spark, Airflow, ETL/ELT, Batch Processing, Reconciliation, Data Validation

•Front-End: JavaScript, TypeScript, HTML/CSS, Flask/Jinja web tools, Tableau dashboards

•AI: Azure AI services (Microsoft Certified Azure AI Developer)

•APIs & Integration: REST, OpenAPI/Swagger, OAuth 2.0, JWT, JSON, XML, Kafka, RabbitMQ

•Databases: PostgreSQL, Oracle, SQL Server, MySQL, MongoDB, Redis, Amazon Redshift

•Cloud & DevOps: AWS (S3, Lambda, ECS, EKS, Glue, CloudWatch), Docker, Kubernetes, Terraform, Jenkins, GitHub Actions, CI/CD

•Testing & Quality: PyTest, unittest, contract testing, mocking/fixtures, code reviews, Git, Jira, Confluence, Agile/Scrum

•Domain: Banking & financial services, insurance, retail; financial reconciliation, operational and financial reporting

PROFESSIONAL EXPERIENCE

Capital One – McLean, VA March 2024 – Present

Senior Python Developer AI/ML

•Develop and modernize Python microservices supporting account servicing, transaction workflows, and financial reporting integrations across internal banking applications.

•Refactored shared logic into reusable service components (authentication, database sessions, validation, error handling), improving maintainability and giving teams consistent, scalable service behavior.

•Automate reconciliation workflows that compare source events, account records, processing outcomes, and reporting totals, ensuring integrity and accuracy of financial outputs.

•Build Pandas-based reconciliation reports comparing event counts, transaction states, and database records, helping operations investigate and resolve processing differences quickly.

•Monitor and troubleshoot business-critical processing runs using structured logging, correlation IDs, metrics, tracing, and CloudWatch alerts; document root causes and add regression tests for every fix.

•Improve runtime efficiency through PostgreSQL execution-plan reviews, indexing, pagination, Redis caching, and asynchronous Python for independent I/O operations.

•Design REST APIs with Pydantic validation, OAuth 2.0, role-based authorization, and OpenAPI documentation; add contract tests so downstream teams catch breaking changes before release.

•Build Kafka event consumers with schema validation, retries, dead-letter routing, and idempotent processing to prevent duplicate financial updates.

•Write PyTest suites covering business rules, API contracts, database transactions, and failure scenarios, maintaining strong automated coverage in CI.

•Support platform upgrades and controlled releases: containerized services on Kubernetes, coordinated PostgreSQL schema migrations, feature flags, and post-deployment verification scripts.

•Build Python utilities generating consistent audit events for financial transactions, configuration changes, and exception resolutions to meet risk and regulatory requirements.

•Partner with product, risk, security, and data teams to translate evolving business requirements into documented, production-ready capabilities.

•Lead code reviews and mentor developers on Python standards, test design, API design, and maintainable service architecture.

Environment: Python, FastAPI, Pandas, Pydantic, SQLAlchemy, PostgreSQL, Redis, Kafka, REST APIs, OAuth 2.0, PyTest, AWS, CloudWatch, Docker, Kubernetes, Terraform, GitHub Actions, Git, Linux.

Verizon – Basking Ridge, NJ January 2021 – Feb 2024

Python Developer

•Developed Python services, Flask and FastAPI endpoints, and automation workflows exposing validated operational data to internal applications and reporting tools.

•Processed high-volume usage data with Python, Pandas, PySpark, and SQL to produce analysis-ready datasets for service monitoring and trend analysis.

•Built Airflow workflows with dependencies, retries, alerting, and automated backfills, and monitored scheduled production runs to keep outputs accurate and on time.

•Implemented data-quality rules for missing identifiers, duplicates, invalid timestamps, and unexpected volumes, with exception reporting for fast investigation.

•Profiled and load-tested Python and Spark jobs, tuning partitioning, shuffle behavior, joins, and storage formats to improve throughput on large datasets.

•Traced discrepancies between source totals and downstream dashboards across ingestion, transformation, and reporting layers to resolve defects at the root.

•Created reusable Airflow operators and configuration templates, standardizing ingestion, validation, and recovery and reducing duplicated pipeline code.

•Implemented schema-version handling for Kafka payloads so consumers kept working through upstream system changes.

•Added unit and integration tests for transformations, APIs, and event handling, and wrote runbooks covering dependencies, alerts, recovery, and escalation.

Environment: Python, FastAPI, Flask, Pandas, PySpark, Spark SQL, Kafka, Airflow, PostgreSQL, Oracle, REST APIs, Docker, Kubernetes, Jenkins, PyTest, Git, Linux.

Nationwide – Columbus, OH April 2018 – December 2020

Python Developer

•Built Python applications and Flask/Django REST APIs supporting policy servicing, claims, payments, and operational reporting.

•Created ETL pipelines in Python, Pandas, and SQL to standardize data from databases, APIs, spreadsheets, and flat files.

•Implemented reconciliation rules comparing source and target counts, financial amounts, payment totals, and status codes to identify exceptions.

•Modernized legacy scripts by documenting existing business rules, converting logic into reusable, tested components, and validating outputs side by side.

•Developed Celery background tasks for scheduled processing, long-running calculations, and retryable integrations, with queue and failure metrics.

•Wrote optimized SQL, stored procedures, and views; used execution plans and indexing to resolve slow queries and reporting bottlenecks.

•Applied database transaction handling to prevent partial updates in multi-step claim and payment workflows.

•Built PyTest and unittest coverage with reusable fixtures and mocked services for business rules, APIs, file parsing, and database transactions.

•Applied authentication, authorization, data masking, and audit logging for customer and financial data.

Environment: Python, Django, Flask, Celery, Pandas, SQL, PostgreSQL, Oracle, REST APIs, JSON, XML, PyTest, unittest, Docker, Jenkins, Git, Linux, Jira.

Target Corporation – Minneapolis, MN March 2015 – March 2018

Big Data Developer

•Developed Flask-based internal web tools that let business users and analysts search records, review data-quality exceptions, and download reports.

•Used Pandas and NumPy to prepare sales trends, product-level summaries, and store comparisons, and performed trend and variance analysis across sales, inventory, and source transactions.

•Created SQL reconciliation reports comparing store-level sales totals with warehouse aggregates and finance reporting outputs.

•Replaced manual spreadsheet transformations with documented, automated Python and SQL processing, improving accuracy and turnaround of recurring reports.

•Supported promotional A/B analysis by preparing treatment and comparison datasets and validating eligibility rules and outcome measures.

•Built Tableau views for sales performance, inventory movement, promotion results, and store-level exceptions.

•Worked with merchandising, supply-chain, and finance teams to clarify KPI definitions and ensure calculations matched approved business rules.

Environment: Python, Flask, Pandas, NumPy, SQL, PostgreSQL, MySQL, ETL, Excel, Tableau, Linux, Shell Scripting, Git, Jenkins, Jira.

EDUCATION

•Master’s in Computer Science – University of Chicago, December 2014

•Bachelor of Technology – Computer Science & Engineering, GMR Institute of Technology, India, 2011

CERTIFICATIONS

•Microsoft Certified: Azure AI Cloud Developer Associate

•PCAP – Certified Associate Python Programmer

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