Aditi Singhal

Data Engineer

India2 yrs 9 mos experience

Highly Stable

Key Highlights

Reduced data processing time by 35% with optimized ETL pipelines.
Improved data availability SLAs by 25% through collaboration.
Implemented CI/CD workflows, cutting deployment time by 50%.

Stackforce AI infers this person is a Data Engineer with expertise in ETL and machine learning solutions.

Contact

aditi.singhal@adp.com LinkedIn

Skills

Core Skills

Data EngineeringEtlCi/cdMachine Learning

Other Skills

AWS EC2AWS S3Agile MethodologiesAgile Project ManagementAmazon S3Apache KafkaApache SparkAzure Data FactoryAzure DatabricksBusiness Intelligence (BI)C (Programming Language)CollaborationCommunicationContinuous Integration and Continuous Delivery (CI/CD)Core Java

About

ADP India focuses on delivering cutting-edge data engineering solutions. Contributed to designing and optimizing over 10 ETL pipelines using PySpark on Databricks, reducing data processing time by 35%. Collaborated with cross-functional teams to streamline data ingestion processes, improving data availability SLAs by 25%. Enhanced error handling and performance tuning, resulting in a 30% reduction in processing failures. With a B.Tech in Computer Science from Manav Rachna University, expertise lies in managing large-scale data processing, building secure CI/CD workflows, and leveraging tools like MongoDB, Jenkins, and Docker. Committed to advancing operational efficiency, enabling actionable insights, and empowering teams through scalable and sustainable solutions.

Experience

2 yrs 9 mos

Total Experience

2 yrs 9 mos

Average Tenure

2 yrs 9 mos

Current Experience

Adp

Data Engineer

Sep 2023 – Present · 2 yrs 9 mos

Designed and optimized 10+ scalable ETL pipelines using PySpark on Databricks, reducing data processing time by 35%.
Created flexible MongoDB schemas, improving downstream data querying speed by 40%.
Collaborated with 5+ cross-functional teams to streamline data ingestion, resulting in a 25% improvement in data
availability SLAs.
Implemented CI/CD workflows using Bitbucket, Jenkins, and Docker, reducing deployment time by 50%.
Enhanced performance tuning and error handling, leading to a 30% reduction in data processing failures.
Utilized Databricks secret scope to securely manage 100% of environment credentials.
Built Splunk dashboards that enabled proactive issue resolution and reduced MTTR by 20%.

Azure DatabricksPySparkPython (Programming Language)SQLMongoDBData Modeling+7

Girlscript summer of code

Open Source Contributor

May 2023 – Aug 2023 · 3 mos

Worked on a - Crop Advisory App(Link-https://cropai.netlify.app/)
Developed and optimized image classification pipelines using TensorFlow and the PlantVillage dataset to identify crop diseases and nutrient deficiencies.
Engineered data preprocessing routines (resizing, normalization, augmentation) to improve model
robustness and accuracy across diverse image inputs.
Designed output transformation logic to convert unstructured model predictions into structured JSON responses for API integration.
Collaborated with backend developers to ensure seamless data flow between frontend uploads, model inference, and result delivery.
Suggested improvements to the model deployment workflow, including batch inference and logging for future data analysis.

Aiw - artificially intelligent workforce

Machine Learning Intern

Jan 2023 – Jun 2023 · 5 mos

Extracted and processed data from 1000+ PDFs and images, converting it into structured JSON for ML pipelines.
Streamlined data formatting process, decreasing manual effort by 60% using Python automation scripts.
Used AWS S3 and EC2 to build scalable storage and compute layers for document classification tasks.