Sr. Google Cloud Platform Data engineer /Google Cloud Platform Architect

Job Overview Job ID: J52137 Job Title: Sr. Google Cloud Platform Data engineer / Google Cloud Platform Architect Location: Atlanta, GA Duration: 24 Months + Extension Hourly Rate: Depending on Experience (DOE) Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, L2-EAD, GC-EAD Employment Type: W-2, 1099, C2C Job Summary We are seeking a skilled Google Cloud Platform Data Engineer to design, build, and optimize data pipelines and analytics solutions in the cloud. The ideal candidate must have hands‑on experience with Google Cloud Platform data services, strong ETL/ELT development skills, and a solid understanding of data architecture, data modeling, data warehousing, and performance optimization. Key Responsibilities Develop ETL/ELT processes to extract data from various sources, transform it, and load it into BigQuery or other target systems. Build and maintain data models, data warehouses, and data lakes for analytics and reporting. Design and implement scalable, secure, and efficient data pipelines on Google Cloud Platform using tools such as Dataflow, Pub/Sub, Cloud Run, Python, and Linux scripting. Optimize BigQuery queries, manage partitioning and clustering, and handle cost optimization. Integrate data from on‑premise and cloud systems using Cloud Storage and APIs. Work closely with DevOps teams to automate deployments using Terraform, Cloud Build, or CI/CD pipelines. Ensure security and compliance by applying IAM roles, encryption, and network controls. Collaborate with data analysts, data scientists, and application teams to deliver high‑quality data solutions. Implement best practices for data quality, monitoring, and governance. Required Skills and Experience Bachelor's degree in Computer Science, Information Technology, or related field. Minimum 8 years of experience in data engineering, preferably in a cloud environment. Minimum 3 years of hands‑on expertise in Google Cloud Platform services, including BigQuery, Cloud Storage, Cloud Run, Dataflow, Cloud SQL, AlloyDB, Cloud Balancer, Pub/Sub, IAM, Logging, and Monitoring. Proficiency in SQL, Python, and Linux scripting. Prior experience with ETL tools such as Datastage, Informatica, or SSIS. Familiarity with data modeling (star/snowflake) and data warehouse concepts. Understanding of CI/CD, version control (Git), and Infrastructure as Code (Terraform). Strong problem‑solving and analytical mindset. Effective communication and collaboration skills. Ability to work in an agile and fast‑paced environment. Google Cloud Platform Professional Data Engineer or Cloud Architect certification is a plus. Equal Opportunity Employer Machine Learning Technologies LLC is an equal‑opportunity employer inclusive of female, minority, disability and veterans (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Machine Learning Technologies LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Machine Learning Technologies LLC require U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract. #J-18808-Ljbffr MACHINE LEARNING TECHNOLOGIES LLC