Pranav Kalwad

Business Analyst

Bengaluru, Karnataka, India1 yr 7 mos experience

Key Highlights

  • Expert in designing scalable data pipelines.
  • Proven track record in optimizing ETL processes.
  • Strong background in cloud-based data warehousing solutions.
Stackforce AI infers this person is a Data Engineer specializing in cloud data solutions for enterprise applications.

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Skills

Core Skills

Data EngineeringCloud Data WarehousingEtl

Other Skills

AirflowAmazon Web Services (AWS)Continuous Integration and Continuous Delivery (CI/CD)Data ModelingData WarehousingDatabricksDistributed SystemsGitGitHubGrafanaMySQLPySparkPythonRedshiftSQL

Experience

Phdata

Associate Data Engineer

Aug 2024Present · 1 yr 7 mos · Bangalore Urban, Karnataka, India · Hybrid

  • Project: Data Mesh Foundation(Biotechnology Research)
  • Engineered generic incremental macros 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 leveraging dbt materialization configs, achieving an 80% reduction in model runtime and decreasing compute costs.
  • Orchestrated a TDD paradigm across ~600 models in the Data Mesh for automated data quality checks (count, metadata, data mismatch), ensuring high data integrity.
  • Leveraged a Snowflake Secure Share to abstract critical business logic, ensuring a "single source of truth" and enabling domain teams to autonomously own their data products.
  • Project: Multi-Engine Platform(HRMS)
  • Engineered multi-engine dbt macros leveraging Snowflake and Redshift adapters to achieve platform portability, creating reusable components and significantly reducing code duplication.
  • 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%.
  • Implemented a proactive governance utility using dbt Great Expectations and Grafana to resolve stale data issues and reduce the Mean Time to Resolution (MTTR).
  • Engineered a Python script utilizing Snowpark and cloud staging (GET/PUT) to automate the chunked, parallel replication of ~10M+ row tables across Snowflake accounts.
  • Developed a POC integrating Mapbox API via Snowflake External Functions and custom UDFs to unlock advanced spatial analytics for clients.
  • Authored technical blog on Snowflake architecture and compliance for government agencies, securing 1,000+ views.https://tinyurl.com/5bth5n35
  • Engineered Agentic AI with phData toolkit for MS SQL to Snowflake translation, reducing manual debugging by 40% for thousands of Stored Procedures.
SnowflakeDatabricksAirflowPythonSQLETL+4

Education

PES University

Bachelor of Technology - BTech — Computer Science

Jan 2020Jan 2024

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