Ritika Lahariya

I’m a highly motivated Data Engineer with 5 years of experience building scalable data pipelines and optimizing ETL workflows. I’m skilled in SQL, Python, Spark, and cloud platforms like AWS and GCP, and I enjoy turning raw data into actionable insights that help teams make smarter decisions.

At SSr Adv Globant (nov 2024 - present), I built a scalable data pipeline that processes usage logs stored in S3, with workflows managed using Airflow DAGs written in Python. I used Apache Spark on AWS EKS for processing and aggregations at scale, storing results as partitioned Parquet files in S3 and date-partitioned tables in Snowflake and Iceberg. I also created a flexible ingestion layer using MongoDB, AWS Step Functions, and Lambda, and implemented OOP-based Python scripts to compare user profiles against business rules and automatically trigger personalized product suggestions.

Earlier, at L1 Publicis Sapient (Feb 2024 - nov 2024), I collaborated with cross-functional teams—data scientists, software engineers, analysts, and business stakeholders—to align data solutions with business needs. I designed and implemented a supply chain management data ingestion pipeline using GitLab CI/CD, Apache Airflow, Python, and Google BigQuery, and I troubleshoot and debug data-related issues while implementing fixes to prevent recurrence.

Before that, at Infosys Ltd. (2020 - Feb 2024) as a Specialist Programmer, I designed and built ETL pipelines using Scala Spark for transformations and scheduled them with Airflow DAGs using Python as the scripting language. I ingested data from multiple sources, performed transformations before loading into data warehouses like BigQuery, and worked across GCP core services such as Google Cloud Storage, Google Dataproc, and Airflow—following Agile engineering practices to deliver reliably.