Data Engineer (Iam Data Lake, Google Cloud Platform)

TL;DR

Data Engineer (IAM Data Lake, Google Cloud Platform): Supports IAM Data Lake and Data Engineering initiatives, focused on building and enhancing a modern enterprise data lake on Google Cloud Platform (GCP) with an accent on designing scalable ingestion pipelines and managing big data architectures. Focus on data governance, security, and access controls align with IAM requirements, as well as CI/CD automation and documentation.

Location: Irving, TX (Preferred) | Ohio (Alternate). Work Type: Onsite/Hybrid (as required)

Salary: null

Company

hirify.global is a company provides staffing services.

What you will do

• Design, build, and maintain a scalable IAM-focused Data Lake on Google Cloud Platform.
• Develop and optimize data pipelines for both batch and real-time ingestion.
• Implement ingestion frameworks leveraging Airflow, PySpark, and GCP-native tools.
• Build streaming architectures using Pub/Sub, supporting event-driven ingestion patterns.
• Ensure data is properly structured and exposed through curated datasets, APIs, and analytical views.
• Collaborate with cross-functional teams to ensure data governance, security, and access controls align with IAM requirements.

Requirements

• 4–6+ years of Data Engineering experience in large-scale environments.
• Strong hands-on experience building Data Lakes on Google Cloud Platform (GCP).
• Expertise in developing pipelines using Apache Airflow, PySpark, and Big data processing frameworks.
• Solid knowledge of the Hadoop ecosystem, with HDFS experience highly desirable.
• Experience with APIs and data exposure patterns, CI/CD pipelines in enterprise environments, and data modeling concepts.
• Strong understanding of GCP architecture, including Bucket structuring and naming standards, Lifecycle management policies, and Access control and security mechanisms.

Nice to have

• Streaming ingestion and event-driven design using Google Pub/Sub.
• Schema registry and governance practices.
• Knowledge of CDC tools/patterns.
• Familiarity with curated analytical dataset development.
• Experience supporting Identity & Access Management (IAM) data domains is a plus.

Culture & Benefits

• Strong problem-solving and analytical mindset.
• Comfortable working in complex enterprise environments.
• Able to collaborate effectively across engineering, security, and governance teams.
• Detail-oriented with a focus on data quality and scalability.