Senior Data Engineer
Remote
- Experience
- 7–12 years
- Employment
- Full-time
- Work mode
- Remote
- Salary
- Not disclosed
- Deadline
- Apply by 1 Nov 2026
- Posted
- 2024-11-15
Required skills
| Skill | Experience | Level |
|---|---|---|
| Human Resources | 6+ years | Intermediate |
| Agile Methodology | 3+ years | Intermediate |
| CI/CD | 3+ years | Intermediate |
| Python | 3+ years | Intermediate |
| SQL | 3+ years | Intermediate |
| Technical Documentation | 2+ years | Intermediate |
| BigQuery | 1+ years | Intermediate |
| GCP | 2+ years | Intermediate |
About the role
● Google Cloud Platform (GCP) Tools:(Mandatory) - BigQuery, Cloud Storage, Dataflow, Cloud Functions, Pub/Sub, Cloud Run, Cloud Composer (Airflow), Cloud Spanner, Bigtable.
● Container Orchestration - Kubernetes (preferred on GKE) and Helm for managing and deploying containerized applications.
● CI/CD and Automation- Jenkins for building CI/CD pipelines to automate deployment and testing of data pipelines.
●Develop and Optimize Pipelines: Write efficient Python and SQL scripts to build data pipelines and ETL/ELT processes. Continuously monitor and optimize data workflows for performance and cost-effectiveness.
● Data Integration and Orchestration: Design workflows to integrate data from various sources using GCP services, and orchestrate complex tasks with Cloud Composer (Apache Airflow)
● Programming Languages- Proficient in Python for data processing and automation, SQL for querying and data manipulation. Experience with Java is a plus.
● DevOps Tools - Familiarity with Terraform or Deployment Manager for Infrastructure as Code (IaC) to manage GCP resources.
● Monitoring and Logging -Experience with Cloud Monitoring, Datadog, or other monitoring solutions to track pipeline performance and ensure operational efficiency.
● Data Engineering Skills Expertise in ETL/ELT pipelines, data modeling, and data integration across large datasets.
● Strong understanding of data warehousing and real-time data processing workflows.
● Strong communication skills to work effectively with cross-functional teams and mentor junior developers. Proven ability to lead in an Agile environment.
● 3+ years of experience as a data engineer, with hands-on experience in Kubernetes, Helm, Python and Jenkins.
● Strong experience building and optimizing data pipelines and services in any cloud platform.
● Proficiency in Python and SQL. Familiarity with Java and Docker is a plus.