Headline

Data Engineer @ Cognite | Forward Deployed Engineer | Solutions Engineer | Enterprise AI Integrations | SQL | Python | PySpark | Databricks | Snowflake | AI Products | Agentic AI | RAG | MCP

About

I operate at the intersection of complex data platforms, enterprise product architecture, and high-value customer outcomes. Currently, as a Data Engineer within the Value Delivery team at Cognite, my role sits dynamically between Solutions Engineering and Forward Deployed Engineering (FDE). My primary mission is driving business value by implementing and scaling the Cognite Data Fusion (CDF) platform across diverse enterprise customer environments. I bridge the gap between core product capabilities and real-world industrial data architecture—translating intricate operational requirements into robust, scalable, and production-ready data solutions. CORE TECHNICAL CAPABILITIES Languages & Core: Python, SQL, PySpark, Bash/Shell Scripting Data Warehousing & Lakehouses: Databricks, Snowflake, AWS Redshift, Delta Lake, Data Modeling Orchestration & Transformation: dbt (Core/Cloud, Slim CI), Apache Airflow, Azure Data Factory (ADF) Big Data & Query Engines: Apache Spark, Trino, Hive, Athena Engineering Standards: CI/CD (Azure DevOps, GitHub Actions), Data Quality Testing (TDD paradigms), Root Cause Analysis (RCA) KEY HIGHLIGHTS & PAST IMPACT Before Cognite, I built enterprise-grade modern data stack platforms as an Associate Data Engineer at phData: Data Mesh & Platform Modernization: Designed automated generic dbt macros and TDD quality assurance frameworks across 600+ models, drastically reducing ETL development times and cutting compute model runtimes by 70%. Multi-Engine Platforms & Synchronization: Engineered cross-platform data loading and SHA2 hash validation utilities between Snowflake and AWS Redshift, accelerating migration self-service and eliminating manual validation hours. Automated Governance & Security: Built Databricks pipelines syncing Azure AD group memberships to Snowflake RBAC via MSAL/OAuth, ensuring automated security enforcement and service account guards. Agentic Frameworks: Leveraged agentic tooling to automate stored procedure migrations and legacy code translation, cutting manual debugging efforts significantly. Feel free to connect or reach out regarding Data Engineering, Forward Deployed Engineering, or Modern Data Stack architecture!

Location

Greater Bengaluru Area

AI stack

claude code

cursor

mcp

claudecode

ChatGPT

Work experience

Data Engineer at Cognite, Aug 2026 - Present · 1 mo, Bengaluru

Associate Data Engineer at phData, Aug 2024 - Jul 2026 · 2 yrs, Bangalore Urban, - Biotechnology Research and Lifesciences: Data Mesh Foundation and Data platform modernization: ∗ Engineered generic incremental macros to automate ETL logic for three major SAP sources during a Data Mesh migration, reducing the development timeline by 100+ days of manual hours. ∗ Optimized complex analytical models by strategically leveraging dbt materialization configurations, achieving an 70% reduction in model runtime and significantly decreasing compute costs. ∗ Orchestrated and implemented a comprehensive TDD paradigm for data quality assurance in the data mesh deploying automated checks (count, metadata, data mismatch) across 600 models, ensuring high data integrity and governance. ∗ Optimized the data delivery lifecycle by implementing a CI/CD process in dbt Cloud, leveraging Slim CI to automate testing and validation on PRs - HRMS: Multi-Engine Data warehouse platform setup ∗ Engineered multi-engine dbt macros leveraging Snowflake and Redshift adapters. This achieved platform portability, created reusable components, and significantly reduced code duplication across the dual data warehouse environment. ∗ Automated dbt model validation using Airflow and Trino, reducing manual data validation time by 120 hours and allowing the team to refocus on development. ∗ Engineered SHA2 hash validation using an Agentic framework (Cursor IDE) between Redshift and Snowflake, reducing false data matches by 90% and increasing cross-platform data integrity. ∗ Designed and implemented a python utility to automate the loading of source tables from Redshift to snowflake , reducing dependency on platform teams and enabling swift, self-service data movement for analytics engineering - Insurance: Data platform modernization ∗ Built a Databricks pipeline that syncs Azure AD group membership to Snowflake roles via MSAL and OAuth, auto-generating and executing CREATE/GRANT/REVOKE SQL with ownership checks and service account guards to prevent unintended deletions.

Education

Bachelor of Technology - BTech, Computer Science, PES University

Public links

github: https://github.com/PranavKalwadBuild