Meet Patel

Data Engineer with 5+ years of experience designing and optimizing scalable ETL/ELT pipelines, Big Data solutions, and cloud-based data platforms across enterprise environments. Proficient in Python, SQL, Apache Spark, Hadoop, AWS, and Microsoft Azure, with expertise in batch and real-time data processing, data integration, and workflow automation. Experienced in implementing data quality and governance practices, building analytics-ready datasets, and leveraging Generative AI and LLM-powered workflows to enhance automation, efficiency, and data-driven decision-making.

Data Engineer at HCL Tech (2023-11 – Present)

• Engineered scalable ETL/ELT frameworks using Python, Apache Spark, and SQL to process large number of records and improve data processing efficiency by 40%.
• Architected cloud-based data solutions on AWS, leveraging Amazon S3, AWS Glue, Amazon Redshift, and EC2 to integrate 20+ data sources and reduce data delivery time by 35%.
• Automated orchestration, scheduling, dependency management, and alerting through Apache Airflow, reducing manual intervention by 60% and improving pipeline reliability.
• Built batch and real-time ingestion frameworks by integrating APIs, streaming feeds, and third-party systems, increasing data availability by 45% and supporting enterprise-scale analytics.
• Established robust data quality controls, including validation, cleansing, and monitoring mechanisms, achieving over 98% data accuracy and significantly reducing data discrepancies.
• Designed transformation processes for structured, semi-structured, and unstructured data, enabling scalable reporting and analytics for cross-functional business teams.
• Implemented metadata management, lineage tracking, and audit logging processes, improving data traceability and strengthening governance and compliance initiatives.
• Streamlined development and release processes using Git, Docker, Jenkins, and CI/CD practices, reducing deployment cycles by 30% and improving maintainability across environments.
• Leveraged Generative AI, OpenAI APIs, and LangChain-based workflows to automate data profiling, metadata generation, and anomaly detection, reducing manual analysis effort by 40% and accelerating insight generation.

Junior Data Engineer at Wipro (2020-01 – 2023-08)

• Developed and maintained ETL workflows using Talend and Informatica to support enterprise data migration, integration, and transformation initiatives across 15+ data sources.
• Leveraged Python and SQL to cleanse, validate, and transform large datasets, improving data accuracy and consistency by 20%.
• Designed and supported cloud-based data warehouse solutions on Microsoft Azure using Azure Data Factory, Azure Databricks, and Azure SQL Database to enable scalable reporting and analytics.
• Engineered Big Data frameworks using Apache Spark and Hadoop to ingest and process high-volume structured and semi-structured data, reducing processing time by 25%.
• Monitored and resolved pipeline failures while integrating API-driven data flows, ensuring reliable data availability and minimizing operational disruptions.
• Executed workflow testing, validation, and quality assurance activities to maintain accurate, consistent, and reproducible data across enterprise platforms.
• Created interactive dashboards and reports in Power BI and Tableau, delivering actionable insights and reducing manual reporting efforts by 30%.
• Partnered with senior data engineers and business stakeholders in Agile environments to streamline data models, automate recurring tasks, and enhance platform performance.

Post Graduation Diploma in Business Management – Saskatchewan Polytechnic (2017 – 2018)

Post Graduation Diploma in Mechanical Engineering – Fanshawe College (2016-09 – 2017-05)

Bachelors in Mechanical Engineering – sigma institute of engineering (2011-08 – 2015-06)