Lead Consultant

2 months ago

Noida, India Genpact Full time

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose – the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI.

Inviting applications for the role of Lead Consultant-GenAI Data Engineer

We are seeking a highly skilled and motivated Generative AI Data Engineer to join our innovative team. The ideal candidate will have a strong background in data engineering and experience with Generative AI technologies. As a Generative AI Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and systems for our cutting-edge AI projects.

Responsibilities

Design and develop data pipelines for Generative AI projects by leveraging a combination of technologies, including Vector DB, Graph DB, Airflow, Spark, PySpark, Python, LangChain, AWS Functions, Redshift, and SSIS. This will involve the logical and efficient integration of these tools to create seamless, high-performance data flows that efficiently support the data requirements of our cutting-edge AI initiatives. Collaborate with data scientists, AI researchers, and other stakeholders to understand data requirements and translate them into effective data engineering solutions.

User will be managing movement, organization and quality assessments of large set of data to facilitate the creation of Knowledge base for RAG systems and model training

Demonstrate familiarity with data integration services such as AWS Glue and Azure Data Factory, showcasing the ability to effectively utilize these platforms for seamless data ingestion, transformation, and orchestration across various sources and destinations.

Possess proficiency in constructing data warehouses and data lakes, demonstratinga strong foundation in organizing and consolidating large volumes of structured and unstructured data for efficient storage, retrieval, and analysis.

Optimize and maintain data pipelines to ensure high-performance, reliable, and scalable data processing.

Develop and implement data validation and quality assurance procedures to ensure the accuracy and consistency of the data used in Generative AI projects.

Monitor and troubleshoot data pipeline performance, identify bottlenecks, and implement improvements as necessary.

Stay current with emerging trends and technologies in the fields of data engineering, Generative AI, and related areas to ensure the continued success of our projects.

Collaborate with team members on documentation, knowledge sharing, and best practices for data engineering within a Generative AI context.

Ensure data privacy and security compliance in accordance with industry standards and regulations.

Qualifications we seek in you:

Minimum qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Strong experience with data engineering technologies, including Vector DB, Graph DB, Airflow, Spark, PySpark, Python, langchain, AWS Functions, Redshift, and SSIS.

Strong understanding of data warehousing concepts, ETL processes, and data modeling.

Strong understanding of S3 and code-based scripting to move large volumes of data across application storage layers

Familiarity with Generative AI concepts and technologies, such as GPT-4, Transformers, and other natural language processing techniques.

Excellent problem-solving, analytical, and critical thinking skills.

Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.

Preferred Qualifications/ skills

Knowledge of cloud computing platforms, such as AWS, Azure, or Google Cloud Platform, is a plus.

Experience with big data technologies, such as Hadoop, Hive, or Presto, is a plus.

Familiarity with machine learning frameworks, such as TensorFlow or PyTorch, is a plus.

A continuous learning mindset and a passion for staying up-to-date with the latest advancements in data engineering and Generative AI.

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