Auxo AI - Senior Data Engineer - Google Cloud Platform

Job Description

Description AuxoAI is seeking a Senior Data Engineer to lead the design, development, and optimization of modern data pipelines and cloud-native platforms using Google Cloud Platform (GCP). This role is ideal for someone with deep experience building scalable batch and streaming data workflows, strong hands-on engineering skills, and a drive to mentor junior engineers. Youll work closely with cross-functional teams to build production-grade pipelines using tools like BigQuery, Dataflow, Pub/Sub, Cloud Composer, and Dataform, enabling high-quality data delivery and analytics at scale. Responsibilities Build and optimize batch and streaming data pipelines using Apache Beam (Dataflow) Design and maintain BigQuery datasets using best practices in partitioning, clustering, and materialized views Develop and manage Airflow DAGs in Cloud Composer for workflow orchestration Implement SQL-based transformations using Dataform (or dbt) Leverage Pub/Sub for event-driven ingestion and Cloud Storage for raw/lake layer data architecture Drive engineering best practices across CI/CD, testing, monitoring, and pipeline observability Partner with solution architects and product teams to translate data requirements into technical designs Mentor junior data engineers and support knowledge-sharing across the team Contribute to documentation, code reviews, sprint planning, and agile ceremonies Requirements 5+ years of hands-on experience in data engineering, with at least 2 years on GCP Proven expertise in BigQuery, Dataflow (Apache Beam), Cloud Composer (Airflow) Strong programming skills in Python and/or Java Experience with SQL optimization, data modeling, and pipeline orchestration Familiarity with Git, CI/CD pipelines, and data quality monitoring frameworks Exposure to Dataform, dbt, or similar tools for ELT workflows Solid understanding of data architecture, schema design, and performance tuning Excellent problem-solving and collaboration skills Bonus Skills GCP Professional Data Engineer certification Experience with Vertex AI, Cloud Functions, Dataproc, or real-time streaming architectures Familiarity with data governance tools (e.g., Atlan, Collibra, Dataplex) Exposure to Docker/Kubernetes, API integration, and infrastructure-as-code (Terraform) (ref:hirist.tech)