Note: The job is a remote job and is open to candidates in USA. Masis Staffing Solutions is a major financial company seeking a Data Engineer for a fully remote position. The Data Engineer will design, build, and maintain scalable data pipelines, ensuring data quality and collaborating with cross-functional teams to meet both near-term and long-term objectives.
Responsibilities
- Develop and maintain batch and streaming data pipelines using modern tools and frameworks. Design transformations, optimize performance, and ensure reliable data delivery
- Design and implement scalable and maintainable data models and storage solutions that align with business needs and support efficient querying, analysis, and data integration efforts
- Engage in agile best practices, help refine stories, identify dependencies, and proactively raise risks or concerns to ensure work is completed on time or escalated when needed
- Implement and enforce data quality controls, validation, and compliance standards across pipelines
- Support the deployment, scheduling, and monitoring of data pipelines and workflows to ensure consistent, reliable execution
- Maintain comprehensive documentation and advocate for coding standards, best practices, and reusable components
- Collaborate regularly with cross-functional teams to clarify data requirements, document assumptions, and deliver high-quality solutions. Communicate clearly during stand-ups, design discussion, and retrospectives. Actively contribute to team code reviews and sharing learnings with peers
Skills
- 2-5 years of experience in data engineering, data modeling, and ETL pipelines
- Proficient in SQL and Python for creating, improving, and fixing data pipelines
- Experience with cloud and data platforms, especially Azure and Databricks (Delta Live Tables and Unity Catalog)
- Strong understanding of tools like SnapLogic, Azure Data Factory, and Jenkins for data integration and orchestration
- Practical experience with Terraform for infrastructure as code and managing deployment pipelines
- Experience integrating with APIs
- Knowledge of data quality and monitoring tools, particularly Soda or similar
- Proficient in version control and CI/CD workflows, using tools like GitHub
- Solid understanding of data modeling principles (e.g., dimensional modeling, normalization)
- Comfortable working in agile teams, with a proactive approach to planning, organizing tasks, and collaborating
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