- Data and model pipeline operations : Maintain and run data and model pipelines ingesting, cleaning, and transforming inputs to ensure they're analysis-ready and of the highest quality.

- Customer delivery execution : Partner with cross-functional teams (Platform, Data Science, GIS, etc. ) on deliveries, making sure insights and recommendations are backed by reliable inputs.

- Monitor and improve : Oversee existing tools and workflows, pinpoint performance bottlenecks, and propose enhancements to streamline our platform/ data science models.

- Innovate and iterate : Absorb best practices in data engineering and analytics, bring fresh ideas to the table, and help us iterate rapidly.

Requirements :

- Minimum 3 years of software engineering experience.

- Experience with building, managing, and maintaining data systems (ETL pipelines, etc. ) for distributed, scalable enterprise-grade applications, with experience working with the following tools/technologies, is required.

- Strong working knowledge of SQL is required.

- PostgreSQL with PostGIS would be preferable.

- Data orchestration tools like Airflow, etc.

- AWS services (S3 EC2 ECR, etc. )

- Containerization tools like Docker, etc.

- CI/CD pipeline tools like Jenkins, etc., would be preferable.

- A solid foundation in programming fundamentals, data structures, and algorithms is required.

- Familiarity with Python, Scala, etc., would be preferable

- Experience working in a cross-functional dynamic environment with tight timelines while leading a small team is required.

- Tools/Tech such as Git, Jira, Confluence, etc. would be preferable.

- Self-started with strong problem-solving skills with a keen interest in data engineering, analytics, and machine learning applications.

- Strong writing and verbal communication skills.