Sai Vijitha
@saivijitha
Senior Data Engineer building secure, scalable cloud-native data pipelines.
What I'm looking for
I am a Senior Data Engineer with five years of experience designing and maintaining scalable data pipelines across banking and healthcare domains.
I specialize in cloud-native ETL and data platform work using AWS, Azure, and GCP—building automated, event-driven ingestion, transformation, and cataloging solutions with tools like Glue, ADF, Databricks, Airflow, and Terraform.
My projects emphasized compliance and security (HIPAA, GDPR, PCI-DSS), improved processing performance (examples: 35% faster retrieval, 40% faster PySpark jobs), and reduced reconciliation and release cycles through automation and best practices.
I deliver production-ready data marts, dashboards (Power BI, Tableau, QuickSight) and containerized services with CI/CD, and I collaborate closely with stakeholders to translate business needs into reliable analytics and operational data products.
Experience
Work history, roles, and key accomplishments
Sr Data Engineer
Conifer Health Solutions
Jan 2024 - Present (1 year 11 months)
Designed and maintained automated AWS-based ETL pipelines and data marts for EHR and clinical data, improving data retrieval speeds by 35% and enabling near real-time analytics while ensuring HIPAA compliance.
Built and optimized large-scale PySpark and ADF ETL pipelines for banking data, improving processing performance by 40% and reducing regulatory reconciliation effort by 60% through Delta Lake and data quality controls.
Developed scalable Azure ELT workflows using ADF and Databricks, optimized Synapse queries to reduce latency by 25%, and delivered Delta Lake datasets and Power BI reports while enforcing GDPR and PCI-DSS controls.
Education
Degrees, certifications, and relevant coursework
University of Texas at Arlington
Master of Science, Data Science
2023 - 2024
Completed a Master of Science in Data Science program focusing on data engineering, machine learning, and cloud-based analytics.
Tech stack
Software and tools used professionally
Postman
Amazon Redshift
Azure Synapse
Apache Spark
AWS Glue
Apache Flink
Data Studio
DOMO
Amazon S3
Google Cloud Storage
GitHub
Kubernetes
Amazon EKS
AWS CodePipeline
Jenkins
NumPy
Pandas
PySpark
dbt
MySQL
PostgreSQL
MongoDB
Cassandra
Hadoop
Gmail
Yarn
Databricks
Terraform
Azure DevOps
Jira
Java
TensorFlow
Kafka
RabbitMQ
Azure Monitor
Linux
Windows
Kali Linux
AWS Lambda
Azure Functions
Amazon RDS
Airflow
Root Cause
SQL
Azure Blob Storage
Burp Suite
Nmap
Metasploit
Delta Lake
Bash
Transform
Make
Availability
Location
Authorized to work in
Job categories
Skills
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