Company Description DataOrbit AI is an AI consulting firm focused on helping small and medium investment managers become AI-ready by aligning strategy, data readiness, technology, and execution. The company provides end-to-end support so organizations can adopt AI seamlessly, driving new growth opportunities and operational efficiencies in a cost-effective way. DataOrbit AI develops explicit, forward-looking AI roadmaps and identifies high-impact use cases that deliver measurable business value. Its teams ensure data is accurate, accessible, and well-governed, and design tailored AI solutions and scalable, cloud-native data architectures that support advanced analytics and AI-driven applications from ideation to production.

Role Description This is a full-time, remote Data Engineer role. The Data Engineer will design, build, and maintain scalable data pipelines and ETL processes that support AI and analytics initiatives for investment management clients. Responsibilities include modeling and structuring data for performance and reliability, implementing and optimizing data warehousing solutions, and collaborating with data scientists and AI engineers to enable machine learning and advanced analytics. The role involves monitoring data workflows, ensuring data quality and governance, troubleshooting issues in production environments, and contributing to improvements in data architecture and MLOps practices. The Data Engineer will also document data systems, support stakeholder data needs,



and help standardize best practices across projects.

Qualifications

- Candidates should possess strong skills in core data engineering, including building and maintaining data pipelines and working with distributed data processing frameworks.
- Candidates should possess skills in data modeling and data warehousing to design efficient schemas, optimize queries, and support analytics and AI workloads.
- Candidates should possess skills in Extract Transform Load (ETL) development, including integrating data from multiple sources, transforming datasets, and ensuring data quality and reliability.
- Candidates should possess skills in data analytics, including querying data, generating insights, and collaborating with analytics and AI teams to support business outcomes.
- Proficiency with SQL and at least one programming language commonly used in data engineering (such as Python or Scala).
- Experience with cloud platforms (e.g., AWS, Azure, or GCP) and modern data stack tools (such as Spark, dbt, Airflow, or similar orchestration frameworks).
- Understanding of CI/CD, DevOps, and MLOps practices for deploying and monitoring data and AI systems in production.
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
- Ability to work independently in a remote environment, communicate clearly with technical and non-technical stakeholders, and manage multiple projects and priorities.

📌 Data Engineer (India)
🏢 DataOrbit AI
📍 India