Shasank Periwal

Data Engineer

Pune, Maharashtra, India3 yrs 8 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Achieved 35% cost savings migrating Spark jobs.
Reduced processing costs by 70% with serverless pipeline.
Built event-driven framework processing 10K+ files daily.

Stackforce AI infers this person is a Data Engineer specializing in Fintech and cloud-native data solutions.

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Skills

Core Skills

AwsData EngineeringSoftware Development

Other Skills

AWS GlueAWS LambdaAWS S3Amazon EC2Amazon Elastic MapReduce (EMR)Amazon RedshiftAmazon Web Services (AWS)Apache AirflowApache SparkApache Spark StreamingC++Cascading Style Sheets (CSS)CommunicationDBTData Marts

About

Data Engineer with nearly 3 years of experience designing and deploying scalable data pipelines in cloud-native environments, currently working at LUMIQ. My core expertise lies in PySpark, SQL, AWS (Lambda, S3, EMR, Glue, Redshift and many more), Airflow, DBT and Python, with certifications including AWS Certified Developer – Associate and Snowflake SnowPro Core. At LUMIQ, I led the migration of Spark jobs from Glue to EMR, achieving 35% cost savings, and architected a serverless PDF ingestion pipeline using LLMs, cutting processing costs by 70%. I’ve also built an event-driven transformation framework processing 10K+ files per day and developed custom DBT tests that cut manual QA by 50%. I'm a certified AWS Developer Associate and Snowflake SnowPro Core. While AWS is my core strength, I also have hands-on experience with Azure and GCP, adding cross-cloud flexibility to my engineering toolkit. I'm passionate about building intelligent, cost-effective data systems and enabling faster analytics at scale. Let’s connect and collaborate on solving data challenges that matter.

Experience

Lumiq

2 roles

Data Engineer

Jul 2023 – Present · 2 yrs 8 mos · Pune, Maharashtra, India · On-site

Architected an AWS serverless pipeline using SAM, Lambda, and S3 for automated PDF financial statement processing, integrating LLMs for intelligent data extraction — reducing costs by 70% for a major banking client.
Migrated Spark jobs from AWS Glue to PySpark on EMR, orchestrated with Apache Airflow — achieving 35% cost savings and improving compute efficiency.
Built a real-time, event-driven pipeline processing over 100K+ files daily, significantly reducing data latency by 40% using AWS S3 event triggers and Lambda.
Developed custom DBT macros to automate complex data quality checks, improving pipeline reliability and cutting manual validation time by 50%.
Implemented Data Vault 2.0 modeling for a financial data warehouse — from raw ingestion to fact/dimension creation in Amazon Redshift — enabling seamless BI analytics consumption.

Amazon EC2SQLAWS LambdaAWS S3AWS GlueApache Airflow+5

Software Engineer Intern

Mar 2023 – Jun 2023 · 3 mos · Pune, Maharashtra, India · On-site

Conducted an in-depth evaluation of Hudi, Iceberg, and Delta Lake, driving optimized CRUD strategies and improving data lake performance by 20%.
Designed a robust retry mechanism for Hive and Spark jobs, increasing pipeline reliability and reducing failure rates by 45%

Apache SparkSQLData Engineering

Bytelearn.com

SWE Intern

Jul 2022 – Nov 2022 · 4 mos · Remote

Developed backend services using Python and JSON to parse, process, and connect microservices across 10+ categories. Optimized chatbot performance, reducing response time by 20% for a smoother user experience.
Tech Stack: Python, Flask, Docker, MongoDB, Git.

PythonJSONGitSoftware Development