
Archit M
Lead Data Engineer
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Technical lead
Media and Marketing • Fulltime
Jan 2022 - Present • 4 yrs 4 mos
Technical Lead with extensive experience designing and scaling cloud‑native data platforms across GCP, AWS, and Azure. Strong expertise in building secure, high‑performance data pipelines using Airflow, BigQuery, Snowflake, Dataproc, Spark, DBT, Dataform, and modern CI/CD automation practices. Currently at Dentsu, delivering large‑scale data solutions for media, automobile, and fintech clients. Built 75+ Airflow DAGs and 15+ Kubernetes workloads, improving distributed processing scalability by 50%. Processed 20B+ data points using BigQuery and Dataform with modular, testable Python code and robust CI/CD pipelines. Led secure cross‑cloud data migrations between AWS S3 and GCP using GCP KMS, encryption, and automated key rotation. Re‑engineered legacy Hadoop/Oozie workflows into cloud‑native Airflow pipelines on GCP Dataproc, processing 210M+ records daily. Implemented high‑volume PySpark batch jobs transforming 550M+ raw records into production datasets with strong reliability, retries, and real‑time alerting. Architected a secure distributed data platform for a payment gateway client, ingesting data from 22+ APIs via Cloud Run into GCS. Managed infrastructure with Terraform (IaC), automated 25+ GitHub Actions workflows, and processed 10M+ transactional records in Snowflake. Implemented envelope encryption and compliance‑ready key management using GCP KMS. Previously at Merkle Inc, optimized large‑scale data pipelines on Azure Databricks and Azure Data Factory, reducing runtimes from 3 days to 8 hours, and delivered containerized AWS microservices processing 50M+ data points, aligned with cloud well‑architected principles. Skilled in Python, SQL, Scala, containerization (Docker, Kubernetes), data governance, performance optimization, and building resilient, production‑grade data systems.