Saify K

Senior Data Engineer with 9+ years of experience building scalable, cloud-native data ecosystems across fintech, healthcare, and SaaS domains. Expert in ETL/ELT pipelines, real-time streaming, big data platforms, and data modeling with hands-on expertise in AWS, Azure, and GCP. Proven record of migrating legacy systems to modern cloud architectures, cutting infrastructure costs by up to 40% and boosting pipeline reliability by 60%.

Skilled in enabling ML/AI workloads, platforms, and real-time analytics by designing high-performance data pipelines and feature stores. Adept at data governance, security, and compliance (HIPAA, PCI-DSS, SOX) while leading cross-functional teams of engineers, data scientists, and business stakeholders. Passionate about building robust, future-ready data platforms that accelerate innovation, drive business value, and empower decision-making.

Lead Data Engineer - Etleap

(2022-08)

• Architected and scaled enterprise-grade AWS lakehouse (S3, Glue, Redshift, EMR), enabling 100+ TB/day ingestion and boosting query performance by 5% for 1,000+ users.
• Developed real-time streaming pipelines with Kafka + Spark, reducing event processing latency from 155.3s, powering mission-critical analytics and ML workflows.
• Migrated 200+ legacy ETL jobs to dbt + Airflow, cutting infrastructure spend by 30% while improving reliability by 60%.
• Built self-service data pipelines that empowered analysts to integrate and transform data without heavy engineering support.
• Partnered with product and data science teams to deliver ML-ready feature stores, improving fraud detection and customer analytics models.
• Executed monitoring and observability with Prometheus, Grafana, and Monte Carlo, ensuring data quality and SLA compliance.

Senior Data Engineer - RTS Labs

(2018-11 - 2022-07)

• Built ETL/ELT pipelines for clinical, claims, and patient data, ensuring HIPAA, HL7, and FHIR compliance.
• Delivered Snowflake & Azure Synapse lakehouse solutions, enabling predictive healthcare analytics and BI dashboards.
• Developed real-time Kafka Spark pipelines reducing clinical alert latency by 50%, supporting patient monitoring systems.
• Implemented data governance frameworks (Collibra, Great Expectations) ensuring accuracy and compliance of healthcare datasets.
• Partnered with clinicians, product managers, and data scientists to improve patient outcomes through actionable insights.
• Automated data quality and lineage reporting, reducing compliance audit effort by 70%.

Data Engineer - CareRev

(2016-03 - 2018-11)

• Built Python + SQL ETL pipelines to integrate data from SaaS applications, CRM, and operational systems for analytics.
• Designed optimized data models (Star Schema, 3NF), improving dashboard query speeds by 10x.
• Automated reporting workflows with Airflow Python, reducing manual reporting workload by 75%.
• Supported migration from SQL Server to AWS Redshift, preparing the foundation for cloud-native analytics.
• Partnered with business stakeholders to develop self-service BI dashboards, enabling faster decision-making.
• Enhanced custom APIs for data exchange, enabling smooth data integration between microservices and data warehouse.

Bachelor of Science - Information System - New Jersey Institute of Technology (NJIT)