Pruthvik Bangalore Ravikumar

Software Engineer - Data @ Workato

About

🌟 Data Engineer | ETL & Pipeline Optimization | Cloud Data Warehousing | Real-Time AnalyticsI’m Pruthvik Bangalore Ravikumar, a results-driven Data Engineer with 3+ years of experience designing and scaling data pipelines, optimizing cloud data warehouses, and enabling real-time analytics across SaaS, EV, fintech, and academic domains. My expertise lies in building reliable, cost-efficient data solutions that power business insights and decision-making.I specialize in ETL pipeline engineering, data quality frameworks, and cloud cost optimization, with strong technical proficiency in Python, SQL, PySpark, Airflow, Kafka, Snowflake, and Redshift. By combining technical depth with business acumen, I’ve delivered measurable improvements in data quality, latency reduction, and revenue impact.🔍 Key Achievements:* Cut ETL runtimes by 88% (4 hrs → 30 min) by optimizing Airflow DAGs.* Implemented Delta Loads from Salesforce to Snowflake, saving 2–3 GB/day while keeping dashboards fresh.* Making medallion architecture more efficient and using dbt to build models* Built a Snowflake FinOps dashboard, saving $250–$300/day in cloud costs.* Automated 20+ data quality checks with Great Expectations across 50+ pipelines, boosting reliability.* Designed real-time Kafka + Airflow pipelines, reducing telemetry latency by 1 hour for proactive monitoring.* Delivered Power BI & Sigma dashboards, driving a 5% revenue lift through actionable SaaS and solar KPIs.* Containerized data services with Docker & Kubernetes, cutting deployment overhead and improving resource efficiency.💡 Skills:Programming: Python, SQL, PySpark, R, C++, JavaFrameworks: Airflow, Dagster, Kafka, Flink, DatabricksCloud & Warehousing: Snowflake, Redshift, AWS (S3, Lambda, Kinesis, Firehose), Azure Data Lake, MongoDB, PostgreSQLCI/CD & DevOps: Docker, Kubernetes, Jenkins, GitHub ActionsData Quality & Observability: Great Expectations, logging frameworks, schema validationVisualization: Power BI, Tableau, Sigma, ExcelOther Tools: JIRA, Confluence, DBT🤝 Let’s Connect:Email: pruthvikravikumar.10@gmail.com

Country

United States

City

Irvine

Industry

Financial Services

Skill

Sigma Business Analytics Software, Snowflake, Salesforce.com, Microsoft Excel, Private Wealth Management, Wealth Management, Family Wealth Management, Risk, Financial Analysis, Research Skills, Market Analysis, Market Research, Power BI, Environmental, Social, and Governance (ESG), Data Collection, Feature Engineering, Investments Risk Management, Kubernetes, Apache Kafka, Financial Statements

Experience

Software Engineer - Data

Workato

2024-12 - Present · 1 yr 10 mos

Palo Alto, CA

▪️ Implemented Delta Load from Salesforce to Snowflake using Dagster, processing only changed records instead of full refreshes , cut runtimes , Snowflake credits and storage reducing 2/3 gigabytes daily while keeping dashboards fresh. ▪️ Implemented SCD Type 2 on key dimensions to preserve history on gold layer in the medallion architecture using dbt, closing prior versions and inserting new ones on change enabling accurate reporting without reloading entire tables. ▪️ Developed standardized logging and monitoring framework for product data pipelines, improving observability and enabling faster triage of pipeline failures, which reduced mean time to resolution of ETL pipelines by 3% ▪️Implemented data quality framework using Great Expectations, automating schema validation and enforcing 20+ business rules across 50+ critical pipelines, improving data reliability and reducing downstream breakages. ▪️Optimized Snowflake data models by restructuring fact/dimension tables, implementing clustering keys, and standardizing schema design, resulting in improved query efficiency and reduced compute costs making it scalable

Data Engineer & Analyst

Advanced Charging Technologies

2023-9 - 2024-8 · 1 yr

▪️Designed and automated modular scalable ETL pipelines using Airflow on GCP with schema validation and idempotent loads to efficiently process large datasets and late-arriving files helping the business not to lose on any data to make business decisions ▪️Implemented real-time processing using Apache Flink consuming from Pub/Sub, storing results in BigQuery, and surfacing alerts via Power BI/Tableau dashboards. Built automated anomaly thresholds to flag failing sensors early which enabled ops team to respond early thus helping us to move forward in implementation quicker ▪️Applied partitioning & clustering (by test_date / device_id), incremental loads, and result-set cache guidance; archived cold data to lower-cost GCS tiers which reduced monthly spend by $180 and unnecessary scans ▪️Built reusable data marts, a documented semantic layer, and onboarded analysts with training sessions which Cut ad-hoc data requests to engineering , enabling self-service analytics and increasing our time by 100% to work on more time sensitive projects

Data Engineer

StoneX Group Inc.

2022-8 - 2023-7 · 1 yr

Bengaluru, Karnataka, India

▪️Improved metadata-driven airflow ETL pipelines using pyspark and migrated pipelines to databricks, reducing financial trading transactions dataset processing time by 12 minutes. ▪️Built Batch data pipelines for murex , EOD dags and intraday end goal was consumed by analytics, used murex open api endpoints , used airflow as orchestrator , azure data lake storage ▪️Backfilled, cleaned, and standardized legacy datasets to align with evolving warehouse schema, reducing inconsistencies in analytics reports and ensuring reliable, trustworthy insights ▪️Implemented Power BI dashboards monitoring trade volumes, revenue & risk for stakeholders to take profitable business decisions ▪️Implemented Slowly Changing Dimension Type 2 (SCD2) transformations in PySpark/Databricks for client and product dimensions, preserving historical attribute changes and ensuring accurate time-based reporting for revenue, risk, and compliance analytics. ▪️Collaborated with stakeholders to design and optimize SQL queries across 30+ tables, ensuring accurate metric calculations while reducing query cost and execution time.

DE

Ember Enterprises

2020-8 - 2021-7 · 1 yr

Bangalore Urban, Karnataka, India

▪️Designed and automated modular scalable ETL pipelines using Airflow on GCP with schema validation and idempotent loads to efficiently process large datasets and late-arriving files helping the business not to lose on any data to make business decisions ▪️Developed unit tests and integration tests for ETL jobs, mocked input data in PySpark local mode, and set up pipeline DAG validation checks in Airflow Dev Environement which reduced the failure rate 99% in productions ▪️Wrote Python/SQL validation scripts (row-count deltas, distribution drift, referential integrity, null & range rules) automated in Airflow which improved the quality of data to carry out business decisions and make business profitable ▪️Built reusable data marts, a documented semantic layer, and onboarded analysts with training sessions which Cut ad-hoc data requests to engineering , enabling self-service analytics and increasing our time by 100% to work on more time sensitive projects