Job Description

STRATEGIC STAFFING SOLUTIONS HAS AN OPENING!

Job Title: Data Engineer – IAM Data Lake (Google Cloud Platform)

Location: Irving, TX (Preferred) | Ohio (Alternate)
Work Type: Onsite/Hybrid (as required)
Contract Term: 12+ Months

Position Overview

We are seeking an experienced Data Engineer to support IAM Data Lake and Data Engineering initiatives, focused on building and enhancing a modern enterprise data lake on the Google Cloud Platform (GCP). This role requires hands-on expertise in designing scalable ingestion pipelines, managing big data architectures, and working with both batch and streaming processing frameworks.

The ideal candidate will have strong experience with GCP-native services, big data tooling, and modern data formats, with additional preference for candidates with exposure to Hadoop/HDFS ecosystems.

Key Responsibilities

• 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.
• Apply best practices for schema design, schema evolution, and versioning across data domains.
• Work with columnar data formats such as Parquet, Avro, and ORC, including compression and performance tuning.
• Support incremental ingestion and Change Data Capture (CDC) methodologies.
• 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.
• Contribute to enterprise development standards through CI/CD automation and documentation.

Required Skills & Experience

• 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
• 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
• Data modeling concepts
• Strong understanding of GCP architecture, including:
• Bucket structuring and naming standards
• Lifecycle management policies
• Access control and security mechanisms

Preferred Technical Expertise

• 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

Tools & Technologies

• Google Cloud Platform (GCP)
• Airflow
• PySpark
• Hadoop / HDFS
• Pub/Sub
• Parquet, Avro, ORC
• CI/CD Automation
• APIs and Data Services

Ideal Candidate Traits

• 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