Twinkle C.

Software Engineer

Pune, Maharashtra, India5 yrs 3 mos experience

Highly Stable

Key Highlights

Three years of hands-on experience in data engineering.
Expertise in building scalable data pipelines on GCP and Azure.
Proven track record in optimizing ETL processes for data quality.

Stackforce AI infers this person is a Data Engineer specializing in cloud-based data solutions for SaaS and Fintech industries.

Contact

Skills

Core Skills

Data EngineeringCloud ComputingData Warehousing

Other Skills

Analytical SkillsApache SparkAzure DatabricksBigQueryBigSQLBigdataBusiness Intelligence ReportingCloud FunctionsCloud StorageData FusionData GovernanceData IntegrationData MonitoringData PipelinesData Quality

About

With three years of hands-on experience as a data Engineer, I specialize in building robust, scalable data pipelines using cloud platforms like Google Cloud Platform (GCP) and Azure. My recent projects include a RealTime Data Migration and Transformation system on GCP, seamlessly handling large datasets from various sources into BigQuery and a User Behavior Analysis and Reporting ETL pipeline on Azure, implementing Medallion architecture and data governance. I bring value through my expertise in efficient data migration, pipeline optimization, and commitment to data quality, making me a strong asset for driving data strategy and innovation.

Experience

5 yrs 3 mos

Total Experience

3 yrs 11 mos

Average Tenure

1 yr 5 mos

Current Experience

Volkswagen group technology solutions india

Senior Software Engineer

Dec 2024 – Present · 1 yr 5 mos · Pune, Maharashtra, India · Hybrid

Google Cloud Platform (GCP)ETL ToolsData IntegrationData QualityData PipelinesBigQuery+7

Devlogic solutions

Data Engineer

Feb 2021 – Jan 2025 · 3 yrs 11 mos

Project: GCP Data Engineering and warehousing(data platform)
Description: Data Engineer on a multi-source data integration project, responsible for designing and optimizing ETL pipelines to migrate large-scale data from Teradata, AWS RDS MySQL, and Google Cloud Storage to BigQuery. Leveraged GCP services like Dataproc, Datastream, and Cloud Functions to handle both real-time and batch data, ensuring high data quality and performance in an end-to-end analytics pipeline supporting business intelligence and reporting needs.
Responsibilities:
Designed and implemented ETL pipelines to migrate data from Teradata, AWS RDS MySQL, and Google Cloud Storage to BigQuery, supporting both batch and real-time data ingestion.
Utilized Google Dataproc for large-scale data processing of Teradata data, including data cleaning, transformation, and reduplication, optimizing job performance through cluster tuning.
Managed real-time data replication from MySQL databases (Mobile App and Payments) using Google Datastream, ensuring low-latency data availability in BigQuery.
Developed and deployed Google Cloud Functions to automate the ingestion of CSV campaign data from Trackier into BigQuery, maintaining data integrity and completeness.
Monitored and orchestrated data pipelines using Google Cloud Composer (Airflow), with proactive alerting via Google Cloud Monitoring for error handling and incident response.
Performed query optimization and validation in BigQuery to support efficient data analysis and reporting for business intelligence applications.
Project: Financial Intelligence Unit (FIU360)
Description: Enterprise data warehouse was set up and designed to provide support for various use cases including analytics, processing, storing, and reporting of voluminous changing data using SQL, cloud storage, data fusion, dataproc, Pyspark.
Responsibilities:
Understand the nature and characteristics of data and check data flow.
Developed pipelines for importing data from various RDBMS,