Senior Data Engineer

Candidate Description

Marked by deep cloud expertise, this Senior Data Engineer brings over six years of experience building large-scale, high-performance data platforms across AWS and Azure landscapes. They have delivered robust ETL and real-time streaming solutions spanning Snowflake, Redshift, Delta Lake, and Databricks while supporting diverse sectors such as financial services, retail, and healthcare. Adept at transforming complex, nested datasets, this professional combines strong analytical acumen with a solid engineering foundation to enable actionable insights and data-driven decision-making.

Their technical acumen is demonstrated through proficiency in tools like Azure Data Factory, AWS Glue, Apache Spark, and Airflow, orchestrating end-to-end data pipelines that ingest, cleanse, and enrich billions of records. Leveraging FastAPI micro-services, CI/CD automation via CloudFormation and Azure DevOps, and rigorous data-quality frameworks such as Amazon Deequ, they consistently deliver secure, compliant, and scalable architectures. Key achievements include introducing real-time Kinesis-powered fraud-detection streams at a Technology Company and slashing ETL latency for retail inventory feeds at a Technology Provider.

Combining leadership with hands-on delivery, they mentor cross-functional teams, author comprehensive Confluence playbooks, and collaborate closely with stakeholders to align technical solutions with strategic goals. Their adaptability across consulting environments and vendor ecosystems enables them to tackle complex data challenges while ensuring business continuity and compliance. This individual offers employers a rare blend of cloud engineering depth, stakeholder engagement, and a proven track record of turning raw data into measurable business value.