Mohd Wasim

Data Engineer

Delhi, India4 yrs 7 mos experience

Highly Stable

Key Highlights

Over 4 years of experience in data engineering.
Expertise in building scalable ETL pipelines.
Recognized with Client Champion & Delivery Excellence Awards.

Stackforce AI infers this person is a Data Engineering professional with expertise in cloud-based big data solutions.

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Skills

Core Skills

Data EngineeringBig DataEtlData IngestionCloud Computing

Other Skills

Data ArchitectsPySparkGoogle Cloud Platform (GCP)AirflowGoogle Cloud StorageBigQueryAWSData MonitoringData LoadingmysqlExtractTransformLoad (ETL)DataprocGoogle BigQuery

About

Data Engineer with 4+ years of experience in designing, building, and optimizing scalable data pipelines and ETL workflows across cloud platforms (GCP, AWS). Skilled in Python, SQL, and PySpark with expertise in data warehousing, cloud migration, and big data processing. Seeking to contribute technical expertise in a cross-functional teams to deliver cost-effective, high-performance data solutions.

Experience

4 yrs 7 mos

Total Experience

2 yrs

Average Tenure

5 mos

Current Experience

Wipro

Senior Data Engineer

Dec 2025 – Present · 5 mos · Noida, Uttar Pradesh, India · Hybrid

Data ArchitectsPySparkData EngineeringBig Data

Globallogic

Data Engineer

Dec 2024 – Dec 2025 · 1 yr · Gurugram, Haryana, India · On-site

Mentored a team to ingest 27,000 school entities (72 attributes each) into Google Cloud Storage via Airflow pipelines.
Developed PySpark scripts for deduplication, normalization, geocoding, and schema validation, boosting operational efficiency by ~30%.
Built ETL pipelines to transform and load data into BigQuery for Google’s search result panel.
Automated workflows, reducing manual intervention by ~70%.
Partnered with Google solution architects to design scalable and robust ETL architecture.

PySparkGoogle Cloud Platform (GCP)Data EngineeringETL

Infosys

Data Engineer

Oct 2021 – Dec 2024 · 3 yrs 2 mos · Noida, Uttar Pradesh, India · Hybrid

Built and maintained ETL pipelines on GCP (BigQuery, GCS, Dataproc, Airflow) and AWS (Redshift,Glue,S3,EC2), processing 10TB+ daily.
Migrated 200+ jobs, reducing costs by ~$15/job/day and improving data ingestion time by 30%.
Automated deployments with CI/CD, cutting cycle time by 50%.
Ensured 99.9% data accuracy, validated business-critical data, and authored 10+ technical design documents.
Recognized with Client Champion & Delivery Excellence Awards

PySparkGoogle Cloud Platform (GCP)Data EngineeringETL