Sep 2023 – Jan 2026 · 2 yrs 4 mos · Pune, Maharashtra, India · On-site

• 1. Spearheaded the development of advanced scanners, achieving extensive vulnerability assessments across thousands of websites.
• 2. Successfully scaled operations to 7,000 daily domain scans using a Kubernetes-driven approach, showcasing exceptional proficiency in handling large data sets.
• 3. Implemented visibility and traceability frameworks for the scanning platform, substantially boosting system reliability and enhancing operational efficiency.

Mar 2023 – Sep 2023 · 6 mos · Remote

• 1. Initiated and directed the first-ever transition of data processing frameworks from on-premises databases to Databricks within Azure, achieving a groundbreaking enhancement in data handling efficiency and insight generation.
• 2. Orchestrated the development and deployment of innovative data ingestion methodologies utilizing PySpark, SQL, Parquet, Delta Tables, and Autoloader, leading to significant improvements in processing speed and data integrity.
• 3. Devised and propagated novel Python design patterns, slashing the average development timeframe by 87.5% per sprint for each developer, thereby expediting product development cycles and elevating team performance in a pioneering Databricks environment.

Feb 2021 – Sep 2023 · 2 yrs 7 mos · Remote

• 1. Engineered and optimized data pipelines for the ingestion and processing of petabytes of data, facilitating the handling and analysis of vast datasets with enhanced efficiency.
• 2. Achieved over $4 million in savings through the strategic integration of multiple heterogeneous data sources into a consolidated framework via advanced ETL processes, significantly improving data accessibility and usability.
• 3. Designed and implemented comprehensive data models to classify and refine raw data into structured formats (Bronze, Silver, and Gold levels), enabling more effective data utilization and analysis.
• 4. Leveraged Python and Airflow to implement real-time monitoring of data ingestion processes across all production environments, ensuring immediate issue identification and notification for developers and business stakeholders, thus minimizing downtime and enhancing decision-making capabilities.

Jul 2019 – Feb 2021 · 1 yr 7 mos · Remote

• 1. Pioneered an incident prediction framework within ServiceNow, employing Natural Language Processing (NLP) to analyze historical incident descriptions. This innovative approach enabled the prediction of the most suitable team for incident resolution based on past data, dramatically reducing the resolution time from 8 days to 3 days. This efficiency gain was achieved by significantly minimizing the need for incident reassignments.
• 2. Acquired in-depth knowledge and hands-on experience with Massively Parallel Processing (MPP) systems, including Teradata and Greenplum. This expertise facilitated significant improvements in data storage and querying efficiency, enhancing system performance and scalability.
• 3. Successfully engineered and launched ETL and ELT pipelines within the Data Lake environment, ensuring seamless and efficient data flow across systems.

Jan 2018 – Jun 2018 · 5 mos · India · On-site

• As a Cyber Security Analyst at Miniorange.
• My job involved performing penetration testing to see how vulnerable companys sensitive data was to common phising attacks.
• Developing Python scripts to perform these tests on a regular basis and develop a solution to prevent these attacks.