KiE Square is a leading AIML Company that provides advanced Data Science/Data Engineering Solutions to its clients and drives their Business Intelligence Transformation.

We invite you to join our Core Team of Data Scientists, Data Engineers and AIML Developers who have a sharp analytical bent, have delivered multiple high-value projects while handling large datasets & have built Predictive Models with a natural ability to take responsibility.

In this role you will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.

Responsibilities :

- Design, develop, and maintain data pipelines and ETL processes for efficient data integration and transformation.

- Manage and optimise data storage and data flows on at least 2 of the following cloud ecosystems -GCP, AWS, Azure, Oracle Cloud.

- Work with large-scale datasets and ensure data quality, consistency, and reliability across systems.

Develop and Enhance Cloud Architecture that could be used for New proposals as well as for Data Engineering pipelines, refreshes, automations and integrations.

- Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.

- Mentor junior engineers, provide technical guidance, and contribute to best practices in data engineering.

- Implement data governance, security, and compliance standards.

- Monitor data pipelines, troubleshoot issues, and ensure high availability of data platforms.

- Optimise database performance and ensure cost-effective cloud resource utilisation.

Qualifications :

- Hands-on experience with ETL tools (e.g., Oracle Data Integrator, Informatica, Talend, or similar).

- Strong knowledge of SQL, PL/SQL, and database performance tuning.

- Experience with data warehousing concepts and big data technologies.

- Familiarity with Python or Scala for data processing and automation.

- Experience with streaming data pipelines (e.g., Kafka, Spark Streaming).

- Knowledge of data modeling and data governance best practices.

- Exposure to containerization (Docker, Kubernetes) is a plus.

- Strong analytical and problem-solving abilities.