Headline

Staff Data Engineer| |Data Architect|Designing data platforms at scale - Data Mesh, Medallion Lakehouse, Real-Time Streaming | GCP · BigQuery · PySpark | AI-Assisted Development | Databricks & GCP Certified

About

Senior Data Engineer with 9 years building enterprise-grade data platforms on GCP — from real-time streaming pipelines to semantic analytics layers that power GenAI agents and business-critical KPIs. Currently at EPAM, working with Google on the Universal Data Layer — a Data Mesh semantic analytics platform serving 25,000+ pipelines, where I architect federated governance, metadata-driven cube modeling, and domain-owned metric publishing at Google scale. What I build: Real-time pipelines: Pub/Sub → Dataflow → BigQuery at TB scale Medallion Lakehouse (Bronze/Silver/Gold) on GCP and Databricks Data Mesh platforms with federated governance and data contracts Legacy-to-cloud migrations: Informatica/Oracle → Spark + BigQuery Tech stack: GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Composer, Dataform) · PySpark · Apache Spark · Databricks · Delta Lake · Apache Iceberg · Python · SQL · Airflow · Terraform · Docker · CI/CD AI-augmented delivery: I use AI coding agents (Gemini, GitHub Copilot) for pipeline code generation, automated documentation, and code review — cutting team iteration time by ~30%. Certifications: Databricks Certified Data Engineer Associate (2026) Google Cloud Professional Data Engineer (2025) Google Cloud Certified Cloud Engineer (2023) Portfolio: github.com/shaloommathew-sys

Location

India

AI stack

antigravity

codex

claudecode

Work experience

Senior Data Engineer at EPAM Systems, Jan 2024 - Jun 2026 · 2 yrs 6 mos, Bengaluru, Building scalable cloud-native data platforms on GCP for enterprise clients across FinTech, Retail, and Cloud domains. ▸ Google — Universal Data Layer (UDL) | Apr 2025–Present Architecting a Data Mesh-aligned semantic analytics platform on GCP, enabling domain-owned metric publishing across multiple Google business units — the authoritative source for cloud business KPIs at Google scale. - Designed metadata-driven cube modeling framework with cardinality constraints (ONE_TO_MANY/MANY_TO_ONE) and aggregation-safe metrics - Implemented federated governance with standardized onboarding contracts for 5+ domain teams - Leveraged AI agents to automate semantic model documentation and accelerate onboarding contract generation ▸ Whirlpool — Real-Time IoT Ingestion Platform | Dec 2024–Apr 2025 - Built Pub/Sub → Dataflow → BigQuery pipelines achieving sub-5-minute latency, processing ~500 GB daily - Delivered Bronze→Silver→Gold medallion layers with automated data quality gates — reducing data incidents by ~30% ▸ Deutsche Bank — Legacy to Cloud Migration | Jan 2024–Dec 2024 - Led migration of 50+ Informatica + Oracle pipelines to Spark + BigQuery - Cut release cycle time by ~40% using Cloud Composer (Airflow) DAGs - Reduced data defect rates by ~35% with governance frameworks Key achievements: ✦ Reduced query costs by ~25% via BigQuery partitioning & clustering ✦ Cut dev iteration time ~30% using AI coding agents (Gemini, Copilot) ✦ Mentored 4–6 engineers across client delivery teams

Data Engineer at Tata Consultancy Services, May 2021 - Nov 2023 · 2 yrs 7 mos, Kochi, Migrated enterprise data warehouses from Oracle & Teradata to BigQuery, modernizing analytics infrastructure for large-scale workloads. ▸ Priceline — DWH Cloud Migration | May 2021–Nov 2023 - Converted 50+ Informatica jobs to PySpark pipelines on Dataproc — reducing infrastructure costs by ~45% - Implemented SCD Type 1 & 2, incremental ELT, reconciliation checks — achieving 99.5% data accuracy post-migration - Optimized BigQuery datasets (partitioning, clustering, materialized views) across 10+ business domains serving 200+ daily users - Built reusable PySpark transformation frameworks across 3 delivery squads - Maintained 30+ Airflow DAGs with SLA enforcement and data validation Extensive expertise in developing and deploying ETL processes, utilizing GCP services such as BigQuery, Cloud Storage, Dataflow, Dataproc, and Apache Airflow.

Data Engineer at Nuvento Inc, May 2020 - Apr 2021 · 1 yr, Kochi, ETL Developer skilled in designing and implementing robust data integration solutions. Proficient in handling data extraction, transformation, and loading processes, ensuring accuracy and efficiency. Adept at optimizing ETL workflows to streamline data pipelines and support data-driven decision-making within organizations.

Data Warehousing Specialist at UST Global, Jun 2018 - Apr 2020 · 1 yr 11 mos, Trivandrum, Kerala, Built enterprise ETL pipelines and dimensional data models for retail analytics on Teradata & Oracle. ▸ H-E-B Grocery — Retail Data Warehouse - Designed Star/Snowflake schema models improving query performance ~30% - Implemented SCD Type 2 and optimized ETL workflows — reducing nightly batch time by 20% - Automated ingestion workflows via Shell scripting, reducing manual effort by ~50%

ETL Developer at Cognizant, Jan 2018 - Jun 2018 · 6 mos, Chennai Area, India, Informatica Developer with a proven track record in designing, developing, and deploying ETL solutions using Informatica PowerCenter. Skilled in extracting, transforming, and loading data from various sources into target systems, ensuring data accuracy and reliability. Experienced in optimizing workflows, creating mappings, and implementing best practices to enhance ETL performance and streamline data integration processes.

Program Analyst Trainee at Cognizant, Jan 2017 - Jan 2018 · 1 yr 1 mo, Chennai Area, India

Intern at Cognizant, Aug 2016 - Dec 2016 · 5 mos, Chennai Area, India

Education

Bachelor of Technology - BTech, Computer Science, Cochin University of Science and Technology

Public links

github: https://github.com/shaloommathew-sys