Prerna S.

Software Engineer

Bengaluru, Karnataka, India7 yrs 8 mos experience

Most Likely To Switch

Key Highlights

Expert in building scalable data pipelines.
Proficient in cloud-native data engineering.
Strong focus on data quality and performance.

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

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Skills

Core Skills

Data EngineeringCloud Data ArchitectureEtl Development

Other Skills

API DevelopmentAb InitioAngularJSApacheApache KafkaApache Spark StreamingAzure Cosmos DBAzure Data FactoryAzure Data LakeAzure SQLAzure servicesBig DataC#CI/CD pipelinesCascading Style Sheets (CSS)

About

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.

Experience

7 yrs 8 mos

Total Experience

2 yrs

Average Tenure

2 yrs 11 mos

Current Experience

Epam systems

Senior Data Engineer

Jun 2023 – Present · 2 yrs 11 mos · Gurugram, Haryana, India · Remote

Developed and managed Delta Lake tables for efficient big data processing and analytics.
Implemented merge logic for data integration and performed complex data transformations.
Designed end-to-end scalable CI/CD pipelines leveraging Azure components like Spark Streaming and Azure Data Factory.

Delta Lakebig data processingdata integrationdata transformationsCI/CD pipelinesAzure Data Factory+3

Ticketmaster

Data Engineer

Oct 2022 – Oct 2023 · 1 yr · Gurugram, Haryana, India · Remote

Built scalable data pipelines using PySpark, SQL, and Python for Ticketmaster.
Implemented Delta Lake, Databricks, and Azure services for ETL and real-time streaming.
Enhanced data quality and efficiency, focusing on clean code and solutions.

PySparkSQLPythonDelta LakeDatabricksAzure services+2

Publicis sapient

Associate Data Engineer L2

May 2021 – Oct 2022 · 1 yr 5 mos · Bangalore Urban, Karnataka, India

In my role as an Associate Data Engineer L2 at Publicis Sapient in Bangalore, Karnataka, I specialized in building scalable data pipelines using PySpark, SQL, and Python. With a strong focus on ETL and data quality, I implemented real-time streaming solutions to optimize data processing. My expertise with Delta Lake, Databricks, and Azure services allowed me to create efficient and reliable data solutions.

PySparkSQLPythonDelta LakeDatabricksAzure services+2