Sophiya Rijal
@sophiyarijal
Senior Data Engineer specializing in scalable cloud-native data platforms and real-time streaming.
What I'm looking for
I am a Senior Data Engineer with over seven years designing and operating scalable, cloud-native data platforms across retail, banking, and insurance domains.
I have deep experience in distributed systems, real-time streaming, and large-scale batch processing using Spark, Kafka, Hadoop, and cloud services on AWS and Azure, with additional exposure to GCP.
I lead cloud migrations, CI/CD automation, and governance-driven engineering, operationalizing machine learning models and building low-latency streaming pipelines that drive analytics and personalization.
I mentor junior engineers, define technical best practices, and deliver cost-efficient, highly available data architectures leveraging tools like Glue, EMR, Redshift, Terraform, Kubernetes, and monitoring solutions to ensure performance and compliance.
Experience
Work history, roles, and key accomplishments
Senior Data Engineer
Big Lots
Jan 2023 - Present (3 years 1 month)
Architected and operated AWS-native cloud data platforms and real-time streaming pipelines, improving scalability and cost-efficiency while enabling sub-second analytics for customer personalization and ML deployments.
Data Engineer
Associated Bank
Aug 2019 - Nov 2022 (3 years 3 months)
Built and migrated petabyte-scale Spark-based batch and streaming pipelines to cloud platforms, improving reliability and reducing costs while enabling low-latency customer analytics and cross-cloud data availability.
Hadoop ETL Developer
Protective Life Corporation
Nov 2018 - Jun 2019 (7 months)
Designed and maintained distributed ETL and streaming pipelines using Spark, Kafka, and Hadoop ecosystem tools on AWS and on-prem clusters, reducing latency and improving throughput for enterprise analytics.
Education
Degrees, certifications, and relevant coursework
University of North Texas
Bachelor of Science, Data Analytics
Completed a Bachelor's degree focused on data analytics, covering statistical analysis, data visualization, and database fundamentals.
Tech stack
Software and tools used professionally
Amazon Redshift
Apache Spark
AWS Glue
Talend
Amazon EC2
Amazon CloudWatch
Amazon S3
Kubernetes
Jenkins
PySpark
DB
Sqoop
MySQL
PostgreSQL
MongoDB
Hadoop
HBase
Gmail
Spring Boot
Yarn
Databricks
Terraform
AWS CloudFormation
Java
Apache JMeter
Kafka
Amazon SNS
MongoDB Atlas
Grafana
Prometheus
Zookeeper
Solr
Ansible
AWS Lambda
Serverless
Kafka Streams
Apache Storm
Airflow
Amazon EMR
SQL
Azure Blob Storage
Qubole
Factory
Availability
Location
Authorized to work in
Job categories
Skills
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