Full Stack Engineer

Job Description

Mandatory Skill Set - AI Full Stack Developer or AI Engineer.

Note - Immediate to 15 Days only

Senior Full stack Engineer

Full Stack Developers & Data Engineers (Business-Engineering Liaison)

The Full Stack Developers & Data Engineers (Play DSA) is a technical role responsible for building and maintaining the data pipelines that power the Play Digital Services Act (DSA) Datamart. This position is central to ensuring that the massive volume of Play Store event data is ingested, transformed, and organized into a high-performance environment for reporting and analysis.

Your primary responsibility is to turn the Lead Architect's designs into reality—writing the code that moves data from raw logs into a structured, validated, and highly efficient GCP-based semantic layer.

Responsibilities

Pipeline Development: Build, monitor, and maintain robust ETL/ELT pipelines to ingest Play compliance and moderation data into BigQuery.

Datamart Construction: Implement the physical schema (tables, views, and materialized views) for the DSA Datamart based on architectural blueprints.

Data Transformation: Write complex, optimized SQL and utilize tools like dbt or Dataflow to transform raw event telemetry into clean, joinable business dimensions.

Data Quality Automation: Develop automated sanity check scripts to detect data drift, null values, or logic breaks before they reach the reporting layer.

Performance Tuning: Optimize query performance and storage costs by implementing partitioning, clustering, and efficient indexing strategies within BigQuery.

Liaison with Engineering: Work closely with Play backend engineers to understand upstream data changes and ensure pipeline resilience.

Required Qualifications (Must-Have Skills)

GCP Data Stack: Professional experience with Google Cloud Platform, specifically BigQuery, Cloud Composer (Airflow), and Dataflow.

SQL Mastery: Expert-level SQL skills, including window functions, complex joins, and query optimization for petabyte-scale datasets.

Python Proficiency: Strong ability to write Python for data orchestration, automation, and custom API integrations.

Data Modeling Knowledge: Practical experience implementing dimensional models (Star/Snowflake) and managing slowly changing dimensions (SCDs).

Technical Rigor: A test-first mindset with experience in version control (Git) and CI/CD workflows for data.

Location-India