Job Description

Key Roles & Responsibilities

Data Architecture & AI/ML Engineering

ETL/ELT & Data Warehousing: Architect scalable pipelines and high-performance BigQuery databases using advanced modeling, partitioning, and clustering strategies.
Stream & Batch Processing: Implement real-time (Pub/Sub, Dataflow) and batch pipeline solutions to feed analytical and operational workloads.
MLOps & Generative AI: Build MLOps pipelines and orchestrate LLM/Agentic workflows using LangChain, Agent Platform, Pandas, and Airflow.
Dashboards & UIs: Build operational interfaces and analytical dashboards using Apps Script (JavaScript), React, and Looker Studio.

DataOps, Security & Governance

Data Quality & DataOps: Establish automated testing, lineage tracking, and proactive monitoring to detect and fix data anomalies early.
Security & Access Control: Enforce IAM policies, data encryption, and compliance standards (GDPR, HIPAA) across all enterprise data assets.

Optimization & Operational Excellence

Performance & Cost Optimization: Audit and tune query execution, pipeline speed, and storage footprints to keep cloud costs strictly controlled.
L3 Support & RCA: Act as the senior L3 escalation authority for GCP and BigQuery platform issues, driving root-cause analysis and rapid resolution.
Governance & Deprecation: Conduct architecture reviews, manage cloud service deprecations, and ensure solutions align with enterprise security standards.
Agile Execution: Deliver projects using Agile/Kanban methodologies in Jira and enforce version control standards using GitHub.

Experience / knowledge

Core Experience: 4 to 5 years of hands-on experience in Google Big Query, ETL Process, AI & ML Apps, MLOps with a strong emphasis on GCP.
Cloud Platforms: Deep proficiency in Google Cloud Platform (GCP) services and governance tools. Preferably familiarity with multi-cloud environments such as AWS, Microsoft Azure, or Alibaba Cloud.
Programming Languages & Frameworks: Advanced Python (3.10+), Shell Scripting (Linux CLI), and Appscript(JavaScript), FastAPI, Django REST Framework, Pandas, and LangChain.
Databases & ETL Tools: MySQL (8.0+), PostgreSQL (13+), Firestore, BigQuery.
Compute: Cloud Run, Cloud Run Functions, Containers & Registry.
CI/CD & Source Control: GitHub, GitHub Actions, Cloud Build.
OS & Tools: Linux OS (command line proficiency), Jira, Kanban, Looker Studio.
Concepts: REST APIs, XML, and L3 Incident Response/RCA.

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