Sr. Data Science Engineer
Sabre Corporation
- Location
- Bengaluru, Karnataka, India
- Job type
- Full-time
Required skills
- Python
- Airflow
- Apache
- Apache Airflow
- Beam
- BigQuery
- clustering
- code review
- configuration management
- data science
- Dataflow
- GCP
- GCS
- GitHub
- Google Cloud
- Nexus
- SQL
- Terraform
- YAML
About the role
Sabre Corporation
Website:
sabre.com
Job details:
Senior Data Science Engineer
Cloud‑Native Analytics Pipelines (GCP)
Service Time: Typically 7+ years of progressive experience in data engineering, analytics engineering, or applied data science roles
Role Overview
We are seeking a Senior Data Science Engineer to design, build, and operate production‑grade analytics pipelines on Google Cloud Platform. This role spans the full lifecycle—from orchestration and transformation to analytics, ML, and infrastructure—using modern CI/CD and infrastructure‑as‑code practices.
Key Responsibilities
- Build and operate Apache Airflow DAGs on Cloud Composer, including dependencies, scheduling, and testing.
- Develop batch and streaming pipelines using Apache Beam on Cloud Dataflow.
- Design, optimize, and maintain BigQuery datasets, SQL, partitions, clustering, and cost‑efficient query patterns.
- Develop and operationalize BigQuery ML (BQML) models within analytics workflows.
- Manage environment‑aware configuration using YAML across DEV, CERT, and PROD.
- Provision and manage GCP infrastructure using Terraform (GCS, BigQuery, IAM, CMEK).
- Own and extend GitHub Actions pipelines for build, test, and multi‑environment deployment.
- Apply GitHub Copilot to accelerate development, testing, and code review.
- Lead or support schema evolution and BigQuery DDL migration efforts.
Strong
Required Skills
- Python (type hints, clean modules, conventions)
- Apache Airflow
- BigQuery (SQL, DDL, performance, cost optimization)
- BigQuery ML (training, evaluation, inference)
- Google Cloud Platform (GCS, IAM, Composer, Dataflow, CMEK)
Proficient
- Apache Beam
- Terraform (IaC modules, lifecycle management)
- GitHub Actions (CI/CD, artifacts, multi‑env deployment)
- YAML‑based configuration management
- GitHub Copilot / AI‑assisted development
Nice to Have
- Artifact registries (e.g., Nexus) and deployment orchestration tooling
- CMEK‑focused security and encryption patterns
- Large‑scale BigQuery schema evolution and migration experience
- Lakehouse architectures on GCP
- Cross‑repo or multi‑team platform engineering experience
- Integrating BQML models into automated Airflow pipelines
If You Want, I Can Next
- Add a short senior‑level expectations callout (technical leadership, design ownership)
Click on Apply to know more.
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