Data Engineer
Description
Responsibilities
- Build new data acquisition and transformation pipelines using advanced data processing and cloud technologies.
- Collaborate with the broader technology team, including information architecture and data integration teams, to align pipelines with strategic initiatives.
Requirements
- Proficient in programming languages commonly used for data processing, data orchestration and workflow management systems, distributed data processing frameworks, relational database management systems, and big data processing frameworks.
- Experience with large-scale data processing platforms.
- Deep understanding of RESTful services, good API design, and object-oriented programming principles.
- Proficiency in object-oriented or functional scripting languages.
- Good working knowledge of relational and NoSQL databases.
- Experience in maintaining and developing software in production environments utilizing cloud-based tools.
- Strong collaboration and teamwork skills, along with excellent written and verbal communication abilities.
- Self-starter and motivated individual with the ability to thrive in a fast-paced software development environment.
- Agile experience is highly desirable.
- Experience with data warehousing and analytics platforms will be a significant advantage.
- Bachelor's degree in computer science or a related field, with at least 4+ years of professional software development experience.
Technical Expertise
- Data Engineering Expertise: Strong experience in distributed data processing and optimization using modern frameworks.
- Cloud Platforms: Proficient in leveraging cloud services for scalable data solutions, including ETL orchestration, containerized deployments, and data storage.
- Workflow Orchestration: Skilled in designing and managing complex data pipelines and workflows.
- Programming Scripting: Proficient in writing clean, modular, and testable code for data processing tasks.
- Database Management: Solid understanding of both relational and non-relational databases, including data querying and modeling.
- ETL Data Architecture: Proven ability to design and implement robust ETL pipelines and optimize data models for performance and scalability.
Soft Skills
- Excellent communication skills - able to articulate technical concepts to non-technical stakeholders.
- Strong interpersonal skills - collaborative, empathetic, and team-oriented.
- Demonstrated ability to work on challenging projects and go the extra mile to deliver results.
Preferred Qualifications
- Experience with CI/CD pipelines, Github and DevOps practices is must.
- Familiarity with data lake and data warehouse architectures.
- Exposure to real-time data processing frameworks, and observability tools like Grafana is added advantage.