What are the responsibilities and job description for the GCP Data Engineer position at Arkhya Tech. Inc.?
Title : GCP Data Engineer
Location: Bentonville , AR (Onsite)
Job Type- Full Time
Role Overview
We are seeking an experienced GCP Data Engineer to design, build, and optimize large-scale data pipelines and analytics solutions on Google Cloud Platform. The ideal candidate will have strong expertise in distributed data processing, real-time ingestion, ETL/ELT, and end-to-end cloud data architecture.
Key Responsibilities
- Design and develop scalable data pipelines using BigQuery, Dataflow, Dataproc, and Pub/Sub.
- Build batch and streaming ETL solutions using Python, SQL, and Apache Beam.
- Implement data ingestion frameworks connecting APIs, databases, streaming platforms, and third-party systems.
- Develop and maintain data models, data marts, and optimized tables in BigQuery.
- Orchestrate workflows using Cloud Composer or Airflow.
- Ensure data quality, lineage, and governance using best practices and tooling.
- Optimize query performance, storage costs, and pipeline reliability across cloud environments.
- Collaborate with data scientists, analysts, and business teams to deliver reliable datasets and analytics layers.
- Implement infrastructure-as-code solutions using Terraform or Cloud Deployment Manager.
- Monitor pipeline health, troubleshoot failures, and ensure SLAs for critical data flows.
Required Skills
- Strong experience with Python, SQL, and distributed data systems.
- Hands-on expertise with BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Dataproc.
- Solid understanding of ETL/ELT frameworks, data modeling, and performance tuning.
- Experience with Airflow / Cloud Composer for orchestration.
- Familiarity with CI/CD, Git, Docker, and DevOps practices.
- Knowledge of Kafka, Spark, or Beam-based pipelines is a plus.
- Strong problem-solving and communication skills.
Preferred Qualifications
- Experience working in finance, healthcare, or enterprise-grade cloud environments.
- Certifications such as Professional Data Engineer – Google Cloud.
- Knowledge of ML pipelines and integration with AI platforms.