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.

You'll 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 3 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)