Results-driven Data Engineer & Applied AI/ML Engineer with 5+ years of experience designing and
delivering scalable data platforms, real-time streaming pipelines, and cloud-native analytics solutions across
AWS, GCP, a…
Results-driven Data Engineer & Applied AI/ML Engineer with 5+ years of experience designing and
delivering scalable data platforms, real-time streaming pipelines, and cloud-native analytics solutions across
AWS, GCP, and Azure. Proven expertise in building end-to-end ETL/ ELT pipelines, distributed data processing
systems, and high-performance data architectures using Python, SQL, Apache Spark, and modern big data
technologies. Skilled in feature engineering, ML-ready dataset development, LLM-powered data workflows,
and advanced data transformation for AI/ ML applications. Strong track record of developing reliable, scalable,
and analytics-ready data solutions that enable machine learning, business intelligence, and data-driven
decision-making at scale.
Architected and built scalable enterprise data platforms and end-to-end ETL/ ELT pipelines for advanced analytics and ML use cases., Developed high-performance batch and real-time data pipelines leveraging Python, SQL, and Apache Spark., Designed and optimized cloud data warehouses and robust data models to ensure long-term performance and scalability., Managed cross-cloud data workflows across GCP (BigQuery, Dataflow) and Azure (Microsoft Fabric)., Implemented data quality validation, automated monitoring systems, and infrastructure-as-code (IaC) using Terraform., Led the design of enterprise-scale data architectures, ensuring high availability, reliability, and operational efficiency., Collaborated with data scientists and business stakeholders to deliver analytics-ready and AI/ ML-ready datasets., Optimized large-scale data processing workflows, improving pipeline performance and reducing operational costs., Mentored junior engineers and promoted best practices in data engineering, cloud technologies, and AI/ ML data platforms.
Architected and optimized large-scale batch and streaming data pipelines using Apache Spark and distributed data processing frameworks., Strategized and led the development of real-time data systems supporting critical analytics and AI/ ML initiatives., Applied Data Mesh architecture principles to improve data scalability, ownership, and domain-driven governance., Enhanced LLM-powered data transformation pipelines and integrated advanced CI/ CD delivery practices., Streamlined Spark workloads on Kubernetes, improving performance, resource utilization, and infrastructure efficiency., Orchestrated enterprise-grade multi-cloud data platforms across AWS and GCP environments., Established production monitoring, observability, and alerting frameworks using Prometheus and Grafana., Mentored junior engineers and contributed to architectural decisions, performance optimization, and engineering best practices.
Developed and maintained scalable ETL/ ELT pipelines using Python, SQL, and cloud-based data technologies., Designed and optimized data models to support business intelligence, analytics, and AI/ ML workloads., Built automated data transformation workflows, improving data quality and reducing processing time., Engineered feature-ready datasets and supported machine learning model development and deployment processes., Collaborated with data scientists and engineering teams to deliver production-ready AI/ ML data solutions., Implemented monitoring, validation, and performance optimization for enterprise data pipelines., Worked with large-scale structured and unstructured datasets to support advanced analytics initiatives., Contributed to cloud-based data platform development and workflow automation using modern DevOps practices.
Developed and maintained scalable ETL/ ELT pipelines using Python, SQL, and cloud-based data technologies.
Designed and optimized data models to support business intelligence, analytics, and AI/ ML workloads.
Built automated data transformation workflows, improving data quality and reducing processing time.
Engineered feature-ready datasets and supported machine learning model development and deployment processes.
Collaborated with data scientists and engineering teams to deliver production-ready AI/ ML data solutions.
Implemented monitoring, validation, and performance optimization for enterprise data pipelines.
Worked with large-scale structured and unstructured datasets to support advanced analytics initiatives.
Contributed to cloud-based data platform development and workflow automation using modern DevOps practices.
Developed backend data processing solutions using Python, SQL, and PostgreSQL.
Assisted in building scalable ETL workflows and real-time data processing pipelines.
Designed and optimized database queries to improve application performance.
Supported AI/ ML data preparation, feature extraction, and data quality validation.
Contributed to cloud deployments and CI/ CD automation practices.
Developed backend data processing solutions using Python, SQL, and PostgreSQL., Assisted in building scalable ETL workflows and real-time data processing pipelines., Designed and optimized database queries to improve application performance., Supported AI/ ML data preparation, feature extraction, and data quality validation., Contributed to cloud deployments and CI/ CD automation practices.
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