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pratikshaa23

Pratiksha B

@pratikshaa23

Data Engineer

Inde
Anglais
Certaines informations sont présentées en anglais.
À propos de moi
I am a Data Engineer with 3+ years of experience building, migrating, and optimizing scalable data pipelines and cloud data platforms. I have strong expertise in SQL, Python, Snowflake, and Apache Airflow for ETL and ELT workflows, data migrations, and performance optimization.... Plus d’infos

Compétences

p
pratikshaa23
Pratiksha B
hors ligne • 

Voir mes services

Correction de bugs
I will build and optimise scalable data pipelines using snowflake and airflow
De10 $US / projetPlus de détails

Expérience professionnelle

Cognizant

Cognizant

Temps plein • 3 yrs 5 mos

Data Engineer

Aug 2024 - Present • 1 yr 9 mos

Planned and enhanced 10+ production ETL pipelines using Informatica, Talend, and Snowflake for enterprise banking datasets. Migrated legacy Informatica workflows to Talend and Snowflake, ensuring data accuracy and schema consistency. Applied data validation and reconciliation checks, reducing post-migration data issues by ~40%. Conducted end-to-end testing and defect resolution to maintain pipeline reliability. Collaborated with cross-functional teams to meet regulatory, compliance, and delivery requirements.

Programmer Analyst (Associate Data Engineer)

Dec 2023 - Aug 2024 • 8 mos

Improved Snowflake SQL performance and warehouse utilization, increasing query efficiency by ~30% and reducing processing time by ~25%. Designed and enhanced end-to-end ETL pipelines using Apache Airflow and Python for data ingestion and transformation. Implemented retries, alerts, and logging mechanisms to ensure pipeline stability and availability. Enforced data quality checks to detect anomalies, null values, and inconsistencies in production datasets.

Programmer Analyst Trainee

Dec 2022 - Dec 2023 • 1 yr

Enhanced complex SQL transformations in Snowflake to support analytics and reporting use cases. Developed and maintained Informatica PowerCenter mappings for multi-source data ingestion and transformation. Supported production pipelines through validation, issue analysis, and root cause investigation to preserve data integrity.