Key Strengths

Strong expertise in Google Cloud Platform (GCP) data services including BigQuery, Dataflow, Data Fusion, Pub/Sub, and Cloud Storage.
Proven ability to design, implement, and optimize scalable batch and streaming ETL pipelines, with quantifiable improvements in efficiency and cost reduction.
Deep understanding of data warehousing concepts, including Star Schema, Snowflake Schema, and Slowly Changing Dimensions (SCD) for robust data modeling.
Demonstrated experience in data quality assurance, monitoring, error-handling, and performance optimization techniques (partitioning, clustering, query tuning).
Proficiency in CI/CD practices (Git, GitHub, Bitbucket) for data engineering workflows, ensuring efficient code integration and deployment.
Relevant certifications (Google Cloud Certified Professional Data Engineer, Databricks for Data Engineering) validate advanced technical skills.
Experience delivering secure and compliant data solutions, adhering to standards like GDPR and ISO 27001.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate exhibits a strong cultural fit for a modern data engineering role, emphasizing cloud-native solutions, CI/CD, and data governance. Their experience with compliance standards (GDPR, ISO 27001) reflects a commitment to responsible data handling. The breadth of skills across GCP and Azure, coupled with various data processing and visualization tools, indicates adaptability and a continuous learning mindset. The personal project further demonstrates initiative and passion for the field.

Soft Skills & Operational Fit

The candidate demonstrates strong problem-solving abilities through debugging ETL failures and identifying root causes. Their focus on data validation, monitoring, and error-handling highlights attention to detail and a proactive approach to operational stability. Quantifiable achievements in efficiency and cost reduction indicate a business-oriented mindset. Experience with CI/CD and collaboration across teams suggests good teamwork and operational discipline. The personal project showcases initiative and practical application of skills.

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Krishna Pal

Data Engineer

https://www.opentalent.in/krishna-pal

Data Engineer with 2+ years in Cloud Data Engineering & ETL Development

FARIZ INFOSOLUTIONS PVT. LTD.

IndiaMember since May 19, 2026

https://www.opentalent.in/krishna-pal

About

Google Cloud Certified Data Engineer with 2+ years of experience building scalable batch and real-time data pipelines using BigQuery, Dataflow, Data Fusion, and Pub/Sub. Skilled in data modeling, ETL pipeline development, and query optimization. Delivers real-time analytics dashboards and cost-efficient data solutions on GCP.

Top Skills

BigQueryDataflowMonitoring

Skills

BigQueryDataflowData FusionData ModelingGCPCloud StorageData ValidationMonitoringTableauGitGithubCiCdPythonJavaScriptMysqlPostgresqlMongoDBSQLETL PipelinesData Modeling

Education

J.C. Bose University of Science and Technology, Faridabad

B.Tech · Information Technology

August 1, 2020 – June 30, 2024

Experience

FARIZ INFOSOLUTIONS PVT. LTD.

Associate Big Data Engineer

November 1, 2024 – Present

India

JBH Tech Innovation

Junior Engineer

April 1, 2024 – October 1, 2024

India

Projects

Smart Complaint Prioritization & Resolution System (GCP-BASED)

May 19, 2026 – Present

Designed and implemented a real-time complaint management system using Pub/Sub, Cloud Functions, and BigQuery. Built a scalable ETL pipeline for ingesting and processing complaint data with timestamp-based tracking. Developed prioritization logic for high-severity complaints, improving response efficiency. Integrated Cloud Scheduler to trigger alerts for unresolved issues and enable proactive monitoring.

Certifications

Google Cloud Certified Professional Data Engineer

Google Cloud

May 1, 2026 – Present

Databricks for Data Engineering

Databricks

May 1, 2026 – Present

Key Strengths

Strong expertise in Google Cloud Platform (GCP) data services including BigQuery, Dataflow, Data Fusion, Pub/Sub, and Cloud Storage.
Proven ability to design, implement, and optimize scalable batch and streaming ETL pipelines, with quantifiable improvements in efficiency and cost reduction.
Deep understanding of data warehousing concepts, including Star Schema, Snowflake Schema, and Slowly Changing Dimensions (SCD) for robust data modeling.
Demonstrated experience in data quality assurance, monitoring, error-handling, and performance optimization techniques (partitioning, clustering, query tuning).
Proficiency in CI/CD practices (Git, GitHub, Bitbucket) for data engineering workflows, ensuring efficient code integration and deployment.
Relevant certifications (Google Cloud Certified Professional Data Engineer, Databricks for Data Engineering) validate advanced technical skills.
Experience delivering secure and compliant data solutions, adhering to standards like GDPR and ISO 27001.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit