Pranshu Sharma

Data Engineer

Bengaluru, Karnataka, India6 yrs 3 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in building and optimizing data pipelines.
Strong experience with AWS and GCP technologies.
Proven ability to automate workflows and enhance data quality.

Stackforce AI infers this person is a Data Engineer with expertise in SaaS and cloud-based data solutions.

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Skills

Core Skills

Data EngineeringEtl

Other Skills

AWSAirflowAlgorithmsAmazon Web Services (AWS)Apache SparkC (Programming Language)CSSCloud SpannerCloud StorageCustom orchestration toolData ModelingData QualityData StructuresData WarehousingDatabricks

About

Data Engineer with strong problem-solving skills and a quick learner's mindset, not wedded to one particulartechnology/language/framework. Experienced in deployment of Big Data solutions in various ecosystems by leveraging topnotch big data tech stacks, optimizing existing code base, migrating applications, automating workflows, creating monitoringsolutions, and developing robust code. Focused on delivering effective engineering solutions.

Experience

6 yrs 3 mos

Total Experience

3 yrs 1 mo

Average Tenure

3 yrs 9 mos

Current Experience

Nike

2 roles

Senior Data Engineer(Software Engineer III)

Promoted

Nov 2025 – Present · 7 mos · Bengaluru, Karnataka, India · Hybrid

Data Engineer(Software Engineer II)

Aug 2022 – Oct 2025 · 3 yrs 2 mos · Bengaluru, Karnataka, India · Hybrid

As a Data Engineer within Nike's Customer Dimensional Data Product team, I am responsible for developing and maintaining robust data pipelines that provide crucial primary store and customer data. I partner with businessstakeholders and analysts to ensure the delivery of quality data for actionable business insights.
Helped our product team in enhancing and optimising the existing pipelines.
Handling multiple data sources end to end, interacting with product owners to understand and resolve their issues.
Migrate our existing pipelines from older version of Airflow cluster to latest.
Fixing the pipelines and perform root cause analysis for addressing consumer issues.
Tech stacks used to build the data pipeline are like Ariflow, Databricks, Kalfka, Spark, AWS, Hive, Snowflake.

AirflowDatabricksKafkaSparkAWSHive+3

Datagrokr

Data Engineer

Jan 2020 – Jul 2022 · 2 yrs 6 mos · Bengaluru, Karnataka, India

Worked as a data engineer to contribute to a full-fledged project for a petroleum company which includes ingestion of data from various sources and a data-driven decision making approach for the client.
Migrate the existing data pipelines from an orchestration tool to a docker-containerised framework.
Worked with startup’s CEO and managers for hiring the good talent.
Worked with startup’s CEO and managers for hiring the good talent.
Build complex end-to-end pipelines and writing robust code to transform raw data sources into easily accessible models.
Automate the workflows, creating the alerts and dashboards to check the health of tables.
Monitoring the pipelines and perform root cause analysis to create business value from big data.
Tech stacks used here was GCP Big query, Pub/Sub, Cloud spanner, Cloudstorage, pandas, spark, custome orchestration
tool.

GCP BigQueryPub/SubCloud SpannerCloud StoragePandasSpark+3

Grappus

Backend Developer Intern

Jun 2019 – Jul 2019 · 1 mo · Gurgaon, India

Worked as a Backend Develoer Intern to learn about Django which is a python web framework.
Worked on the internal project to create a website using Django.
Contribute to backend team to build REST API using Django rest framework.

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Internship Trainee

May 2018 – Jul 2018 · 2 mos · Jaipur, Rajasthan, India

Worked on integrating docker, ansible, hadoop, spark using python.
Developed a CGI based web portal for a one click set up of HDFS and Map Reduce cluster depending on requirement of client per service.