Data Scientist
1 month ago
Data Engineer Role at Omni Inclusive
Omni Inclusive is seeking a highly skilled Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, developing, and maintaining scalable data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
Key Responsibilities:
- Experience working within the Azure ecosystem, including Azure AI Search, Azure Storage Blob, Azure Postgres, and understanding how to leverage them for data processing, storage, and analytics tasks.
- Ability to preprocess and clean large datasets efficiently using Azure Tools/Python and other data manipulation tools.
- Expertise in working with healthcare data standards (e.g., HIPAA and FHIR), sensitive data, and data masking techniques to mask personally identifiable information (PII) and protected health information (PHI).
- In-depth knowledge of search algorithms, indexing techniques, and retrieval models for effective information retrieval tasks.
- Familiarity with search platforms like Elasticsearch or Azure AI Search.
- Familiarity with chunking techniques and working with vectors and vector databases like Pinecone.
- Ability to design, develop, and maintain scalable data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
- Experience with implementing best practices for data storage, retrieval, and access control to ensure data integrity, security, and compliance with regulatory requirements.
- Ability to implement efficient data processing workflows to support the training and evaluation of solutions using large language models, ensuring reliability, scalability, and performance.
- Ability to proactively identify and address issues related to data quality, pipeline failures, or resource contention, ensuring minimal disruption to systems.
- Experience with large language model frameworks, such as Langchain, and knowledge of how to integrate them into data pipelines for natural language processing tasks.
- Experience working within the Snowflake ecosystem.
- Knowledge of cloud computing principles and experience in deploying, scaling, and monitoring AI solutions on cloud platforms like Snowflake, Azure, and AWS.
- Ability to communicate complex technical concepts effectively to technical and non-technical stakeholders and collaborate with cross-functional teams.
- Analytical mindset with a keen attention to detail, coupled with the ability to solve complex problems efficiently.
- Knowledge of cloud cost management principles and best practices to optimize cloud resource usage and minimize costs.
- Requirements:
- Minimum of 10 years' experience as a data engineer.
- Hands-on experience with Azure Cloud ecosystem.
- Hands-on experience using Python for data manipulation.
- Deep understanding of vectors and vector databases.
- Hands-on experience scaling POC to production.
- Hands-on experience using tools such as Document Intelligence (formerly Azure Form Recognizer), Snowflake, function app, Azure AI Search.
- Experience working with PII/PHI.
- Hands-on experience working with unstructured data.
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