Prerna S. — Software Engineer

Data Engineer | Cloud-Native Pipelines | Databricks | Spark | Azure & AWS I architect scalable, high-performance data pipelines that fuel analytics, reporting, and machine learning. From real-time streaming to large-scale batch processing, I build data systems that just work — fast, reliable, and production-ready. What I do: • Transform messy raw data into trusted, analytics-ready datasets • Design and optimize Spark/PySpark jobs that handle billions of records • Build robust ETL/ELT workflows using Databricks, Azure Data Factory, and AWS Glue • Stream data in real time using Kafka, Delta Live Tables, and modern cloud services • Manage and integrate data across Azure and AWS environments with precision What drives me: • Turning complexity into clarity • Cutting query runtimes by minutes (or hours!) • Building secure, low-latency data flows that scale with confidence • Solving real-world data problems behind the scenes so teams can focus on insights Tech I trust & work with daily: Databricks | Spark / PySpark | Delta Lake | SQL | Azure Data Factory | AWS S3 / Glue | Streaming Pipelines | CI/CD | Data Lakehouse Architecture Whether you’re wrestling with fragmented pipelines, struggling to scale on the cloud, or looking to modernize your data stack — I’m always up for sharing ideas, solving challenges, or just geeking out over distributed systems. 👉 Let’s connect if: • You’re scaling your data platform and need hands-on cloud-native experience • You’re working on a product that’s data-intensive and value performance • You care about data quality, observability, and building things that last Because great data engineering isn’t about the tools — it’s about making data useful.

Stackforce AI infers this person is a Data Engineering expert in cloud-native architectures for analytics and machine learning.

Location: Bengaluru, Karnataka, India

Experience: 7 yrs 6 mos