- Design and implement scalable, fault-tolerant data pipelines using modern ETL tools
- Develop automated data workflows using Apache Airflow, Databricks, or similar platforms
- Implement real-time data streaming solutions using Kafka, Kinesis, or PubSub
- Optimize pipeline performance and maintain data quality standards
- Configure and manage cloud-based data infrastructure (AWS, GCP, Azure)
- Implement data security and compliance measures
- Collaborate with data scientists and analysts to support ML operations
- Monitor pipeline health using observability tools
- Document technical specifications and maintain knowledge bases
Job Description Template
Data Pipeline Developer Job Description Template [2025]
Find expert Data Pipeline Developers who can design, implement, and maintain flexible data pipelines in modern data engineering practices, cloud infrastructure, and AI-driven automation.
In 2025, Data Pipeline Developers must excel in cloud-native architectures, AI-assisted development, and sustainable data practices. They should be proficient in implementing secure, flexible strategies while adhering to data governance standards. This template helps you attract candidates who can leverage modern tools and methodologies to build next-generation data infrastructure.
Job Responsibilities
Essential duties of a Data Pipeline Developer in 2025:
Sample
Required Skills
Core technical requirements for Data Pipeline Developers:
Sample
- Bachelor's degree in Computer Science, Data Engineering, or related field
- 4+ years experience in data pipeline development
- Proficiency in Python, SQL, and shell scripting
- Strong experience with ETL tools and frameworks
- Expertise in cloud platforms (AWS, GCP, Azure)
- Knowledge of data warehousing concepts
- Experience with version control and CI/CD practices
- Understanding of data modeling and architecture
- Familiarity with distributed computing systems
Preferred Skills
Additional valuable qualifications for candidates:
Sample
- Experience with AI-assisted development tools
- Knowledge of MLOps and feature engineering
- Expertise in real-time streaming architectures
- Familiarity with data governance frameworks
- Container orchestration (Kubernetes, Docker)
- Experience with DataOps practices
- Cloud platform certifications
- Knowledge of data privacy regulations
- Experience with graph databases and NoSQL systems
Benefits & Perks
Competitive benefits package for Data Pipeline Developers:
Sample
- Top-tier base salary with performance bonuses
- Remote-first work environment
- Comprehensive health and wellness benefits
- Professional development budget
- Conference attendance opportunities
- Stock options or equity packages
- Flexible working hours
- Regular training on emerging technologies
- Modern tech stack and tools
Why Hire Data Pipeline Developers?
Data Pipeline Developers harness the power of big data through automated, efficient, and reliable data processing systems to enable real-time analytics, ML operations, and data-driven decision making.
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