Chappidi Vishnu

Software Engineer with production experience designing, building, testing, and debugging ETL/ELT pipelines on Google Cloud Platform using Python, SQL, and Bash scripting. Proficient in GCP cloud data services including BigQuery, Cloud Storage, Cloud Data Fusion, Dataflow, Cloud Composer, and Cloud SQL with hands-on expertise in cloud data storage, pipeline orchestration, and API integration. Experienced in applying GitHub Copilot and AI-assisted development workflows to accelerate coding, debugging, testing, and documentation tasks.

Strong analytical and problem-solving skills with a compliance-first, risk-aware engineering mindset — committed to proactive monitoring, sound escalation judgment, and adherence to security and governance requirements aligned with Wells Fargo's engineering standards.

Software Engineer – ETL Pipelines, GCP Cloud & Data Engineering at FIS Clouds (2025-05 – Present)

• Participated in day-to-day ETL and ELT pipeline building on Google Cloud Platform — designing, coding, testing, debugging, and documenting Python-based data pipeline components that process millions of records daily across enterprise GCP cloud data infrastructure.
• Designed and developed production ETL pipelines using Cloud Data Fusion, Dataflow (Apache Beam), and Python scripting to extract data from on-premise PostgreSQL and MySQL databases, transform it through structured business logic, and load it into BigQuery and Cloud Storage for analytical consumption.
• Wrote Python and Bash/Unix scripts for data extraction automation, schema validation, pipeline health checks, file-based data ingestion, and operational monitoring tasks — improving pipeline reliability and reducing manual operational overhead.
• Built and optimized complex SQL queries for BigQuery and PostgreSQL including multi-table joins, window functions, CTEs, aggregations, and incremental load logic — ensuring high-performance, cost-efficient data retrieval and transformation across large-scale analytical datasets.
• Developed RESTful API integrations and JDBC connector services enabling reliable data exchange between enterprise relational database management systems and GCP cloud-native pipeline infrastructure.
• Leveraged GitHub Copilot and AI-assisted development tools for code generation, debugging acceleration, automated documentation drafting, and test case scaffolding — improving individual engineering productivity while critically evaluating all AI-generated outputs for correctness and quality.
• Applied security, compliance, and risk-awareness practices throughout the SDLC — implementing IAM least-privilege access controls, secrets management for database credentials, VPC network isolation, audit logging, and change control procedures aligned with enterprise governance requirements.
• Identified and presented service quality and availability improvement opportunities within the GCP pipeline environment — analyzing pipeline failure patterns, proposing runbook-based resolutions, and escalating systemic issues with structured diagnostic context to meet SLA commitments.
• Automated ETL workflow orchestration using Apache Airflow (Cloud Composer) — implementing parameterized, event-driven DAG schedulers with retry logic, failure alerting, and execution audit trails to ensure reliable, zero-touch pipeline execution.
• Collaborated as a strong team player in agile sprint cycles — participating in code reviews, design discussions, and cross-functional stakeholder communication to deliver software increments on schedule with high quality.

Bachelor of Technology (B.Tech) in Computer Science and Engineering – Siddharth Institute of Engineering and Technology (2020 – 2024)