Data Engineer

4 weeks ago

BangaloreMysore, India MaimsD Technology Full time

Summary :

We are seeking a skilled Data Engineer to join our growing AI team. In this role, you will collaborate closely with our GenAI experts to design, build, and maintain the data pipelines and infrastructure necessary for developing and deploying powerful GenAI models.


Responsibilities :

- Partner with GenAI Data Scientists to understand their data needs and design efficient data pipelines for data collection, pre-processing, and transformation.

- Develop and implement data pipelines using tools like Apache Airflow, Luigi, or Prefect to automate data ingestion, cleaning, and feature engineering tasks.

- Build and manage data infrastructure on the Azure cloud platform to support large-scale GenAI model training and inference.

- Collaborate with DevOps engineers to ensure seamless integration of data pipelines and infrastructure with the GenAI development lifecycle.

- Implement data quality monitoring and alerting systems to ensure data integrity for GenAI models.

- Maintain and optimize existing data pipelines and infrastructure for performance and scalability.

- Stay up-to-date on the latest advancements in big data processing technologies and cloud platforms.

Qualifications :

- Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).

- 3+ years of experience as a Data Engineer or similar role.

- Strong experience with data pipelines, data processing tools, and data wrangling techniques.

- Familiarity with Azure cloud platform is a must.

- Experience with data warehousing and data lake architectures.

- Proficiency in SQL and scripting languages and Python.

- Excellent communication and collaboration skills to work effectively in a cross- functional team.

- A problem-solving mindset and a passion for building robust data infrastructure.

Preferred Skills :

- Experience working with Generative AI models or other machine learning projects.

- Knowledge of data versioning and data lineage management practices.

(ref:hirist.tech)

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