Engineer

Job Summary :

As a GCP Data Engineer, you will be responsible for designing, building, and maintaining scalable data processing systems on Google Cloud Platform (GCP) . You will collaborate with cross-functional teams to ensure data is accessible, reliable, and optimized for analytics and machine learning initiatives.

Key Responsibilities :

Data Pipeline Development :

Design, develop, and maintain ETL / ELT pipelines using tools like Cloud Dataflow , Apache Beam , and Cloud Dataprep .

Implement real-time data streaming solutions using Cloud Pub / Sub or Apache Kafka .

Data Storage & Warehousing :

Manage and optimize storage solutions such as BigQuery , Cloud Storage , and Cloud Spanner .

Design efficient data models and schemas for structured and unstructured data.

Data Integration & Transformation :

Integrate data from multiple sources into unified data lakes or warehouses.

Cleanse, enrich, and transform raw data into analytics-ready formats.

Performance Optimization :

Monitor and troubleshoot data pipelines.

Optimize workflows for scalability, performance, and cost-efficiency.

Security & Compliance :

Implement data governance policies.

Ensure compliance with data protection regulations (e.g., GDPR, HIPAA).

Collaboration & Communication :

Work closely with data scientists, analysts, and business stakeholders.

Translate technical solutions into business insights.

Required Skills :

Proficiency in Python , SQL , and optionally Java or Scala .

Experience with GCP services : BigQuery , Cloud Dataflow , Cloud Storage , Cloud Composer , etc.

Strong understanding of data warehousing , data modeling , and ETL processes .

Familiarity with real-time data processing and streaming architectures .

Knowledge of data governance , security , and compliance standards .

Qualifications :

Bachelor’s degree in Computer Science , Engineering , or related field.

GCP Professional Data Engineer certification (preferred).

2+ years of experience in data engineering, preferably in cloud environments.