
Data Engineer
2 days ago
Role Overview
We are seeking a skilled Data Engineer with 3+ years of hands-on experience in building and managing data pipelines, data models, and cloud-based analytics solutions on
Google Cloud Platform (GCP)
. The ideal candidate will have strong expertise in GCP-native services such as
BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Composer
, along with proven experience in SQL, Python, and ETL/ELT design.
This role requires working closely with data scientists, analysts, and business teams to ensure scalable, reliable, and high-performance data infrastructure.
Key Responsibilities
Data Pipeline Development
Design, build, and optimize scalable ETL/ELT pipelines using GCP services (Dataflow, Composer, Pub/Sub, BigQuery).
Ingest structured and unstructured data from multiple sources into cloud storage and warehouse solutions.
Data Warehousing & Modeling
Develop efficient and optimized data models in BigQuery.
Implement partitioning, clustering, and query optimization for performance and cost efficiency.
Cloud Infrastructure
Work with GCP-native tools for data integration, storage, and analytics.
Ensure high availability, security, and compliance of data systems.
Collaboration & Support
Partner with data scientists, analysts, and application teams to deliver reliable datasets.
Troubleshoot issues, monitor pipelines, and ensure SLAs for data delivery.
Best Practices & Governance
Implement data quality checks, monitoring, and lineage tracking.
- Follow DevOps and CI/CD practices for data engineering projects.
Required Skills & Qualifications
- 3+ years of hands-on experience in data engineering.
Strong expertise in GCP data services:
BigQuery (SQL, performance tuning, cost optimization)
- Dataflow (Apache Beam pipelines)
- Cloud Composer (Airflow orchestration)
- Pub/Sub (streaming ingestion)
Cloud Storage, Dataproc
Proficiency in SQL and Python for data transformation and automation.
- Good knowledge of ETL/ELT design, data modeling, and warehousing principles.
- Experience with Git, CI/CD pipelines, and version control.
- Understanding of data security, IAM, and compliance in cloud environments.
Nice-to-Have Skills
- Familiarity with Terraform/Deployment Manager for IaC (Infrastructure as Code).
- Knowledge of Kafka, Spark, or DBT for advanced data engineering use cases.
Skills: gcp,pipelines,data,data engineering
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