Data Engineer

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.
  

What Were Looking For:

• Proficient in programming languages commonly used for data processing, Data orchestration and workflow management systems, Distributed data processing framework, 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.