Vishnu Reddy
Actively looking for jobs in Data Engineering | Proficient in Azure | GCP | AWS | Databricks | SQL | Python | Hadoop | Snowflake | Azure synapse Analytics | Power BI | ETL
- Role
- Senior Data Engineer at Northern Trust
- Location
- Chicago, IL, US
- LinkedIn followers
- 500 followers
About Vishnu Reddy
With over 8+ years of experience as a Senior Cloud Data Engineer, I specialize in working with cloud platforms like Azure, GCP, and AWS to design and build scalable data solutions that help businesses gain valuable insights and support their digital transformation efforts.I have hands-on experience with cloud technologies such as Azure Data Factory, Databricks, Synapse Analytics, Data Lake Storage, and Power BI, as well as AWS services like Redshift, Glue, EMR, Lambda, and S3. This enables me to create end-to-end data pipelines for integrating, transforming, and analyzing large-scale data efficiently.I focus on building data lakehouse architectures using Delta Lake and connecting them with Azure and AWS environments to simplify data processes and optimize workflows. My skills in PySpark, SQL, and Python allow me to perform complex data transformations, improve performance, and handle real-time data streaming while ensuring data quality and compliance with important standards like HIPAA, GDPR, and FHIR.I prioritize data security by using encryption, managing access controls, and deploying automated solutions with Terraform and CloudFormation. I enjoy working in team environments, using Agile practices to deliver high-quality data solutions that help organizations make informed, data-driven decisions.I am passionate about learning and staying updated on the latest trends in cloud data engineering, big data analytics, and machine learning.
Experience
Senior Data Engineer
Mar 2025 — Present · Chicago, IL, US
Worked on building and scaling cloud-based data platforms using Azure Data Factory (ADF) and Azure Databricks to support enterprise analytics and reporting needs. Designed and implemented end-to-end ETL/ELT pipelines to ingest data from multiple sources, perform transformations using PySpark, and deliver curated datasets to downstream consumers. Collaborated closely with data analysts, business stakeholders, and cloud teams to ensure data quality, reliability, and performance. Optimized Databricks jobs for cost and efficiency, implemented incremental loads, and followed best practices for logging, monitoring, and error handling. Played a key role in modernizing legacy workflows into a scalable Azure data architecture aligned with business goals
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