Headline

Data Engineer | Azure | ADF | Snowflake | PySpark | SQL | Microsoft Fabric | Python | Data Engineering

About

Data Engineer with 1+ year of experience building and optimizing cloud-based data pipelines and data platforms using Azure Data Factory, Azure Data Lake, Snowflake, SQL, Python, Spark and Microsoft Fabric. Experienced in designing ETL/ELT pipelines, data quality frameworks, dimensional modelling and data transformation workflows across enterprise data platforms. Delivered production solutions involving SAP, SQL Server, APIs and large-scale datasets. Key strengths include pipeline optimization, SQL performance tuning, Snowflake transformations, data validation, dynamic ingestion patterns and scalable data processing with Spark. Currently focused on strengthening expertise in Databricks, PySpark, modern data engineering architectures and cloud data platforms.

Location

Bengaluru

AI stack

claude code

codex

gemini

langchain

langgraph

ChatGPT

Work experience

Software Engineer at CoStrategix, Jun 2025 - Present · 1 yr 4 mos, Bengaluru, Karnataka, India, Working as an Associate Software Engineer in a Data Engineering role, building and supporting cloud-based data platforms and production data pipelines. Started with a structured engineering and data-platform training program covering SQL, Python, Azure, data warehousing, ETL/ELT, cloud technologies and modern data engineering practices. Progressed into hands-on project delivery, working with enterprise data sources and production-grade data pipelines. My current work spans: • Designing and developing ETL/ELT pipelines using Azure Data Factory and Azure Data Lake • Building data ingestion and transformation workflows in Snowflake • Working with SQL, Python, Snowflake JavaScript stored procedures and Spark notebooks • Integrating data from SAP HANA, SAP OData, SQL Server, APIs and large structured datasets • Developing dimensional models, fact/dimension tables and downstream data marts • Implementing data quality, validation and reconciliation frameworks • Optimizing pipeline and SQL workloads for performance and resource efficiency • Following engineering practices around Git, documentation, testing, validation and maintainability Across projects, I have focused not only on delivering pipelines but also on understanding the underlying data, identifying bottlenecks, designing reusable solutions and improving reliability and operational efficiency. Alongside core Data Engineering work, I have gained exposure to GenAI and context-enriching agentic AI applications, exploring how intelligent agents can leverage enterprise data and tools to improve data interaction and decision-making. I am continuing to grow toward modern Data Engineering with deeper focus on Python, PySpark, Databricks, Microsoft Fabric, scalable cloud data platforms and data-intensive AI applications.

Education

Bachelor of Engineering - BE, Information science and engineering, Visvesvaraya Technological University

Bachelor of Engineering, Information science and engineering, Jawaharlal Nehru new college of engineering