Job Description

Job Description

AI Data Engineer

Location: Remote or Hybrid

Experience Level: Mid–Senior (4+ years)

About the Role

This role supports the organization’s data, analytics, and AI innovation efforts by building reliable data pipelines, developing machine learning solutions, and improving how information is collected, processed, and used across the business. This person is a collaborative problem-solver who can translate business needs into technical solutions, work confidently across large datasets, and deliver clear, actionable insights that help drive strategic outcomes.

What They Do

• Support innovation projects by facilitating discussions, refining business processes, integrating data sources, and advising on best practices in analytics and AI.
• Build and maintain data architectures, APIs, and pipelines to support both operational systems and AI initiatives.
• Design and implement machine learning models, including developing prompts and AI-driven applications.
• Collaborate with technical and non-technical teams to improve data quality, reporting, and analytics across the organization.
• Manage large, complex datasets and develop tools to extract meaningful insights.
• Automate manual processes, optimize data delivery, and enhance internal infrastructure.
• Create dashboards and visualizations that clearly communicate insights to stakeholders.
• Apply statistical, computational, NLP, and ML techniques to solve business problems.
• Document processes, use version control best practices, and deploy models to production using enterprise platforms such as Azure.
• Ensure data security and privacy across systems, vendors, and applications.

Experience & Skills

• 4+ years in a Data Engineering or DataOps/DevOps role.
• Strong experience with SQL, relational databases, cloud environments (Azure/AWS), and building/optimizing data pipelines.
• Ability to work with structured and unstructured data and perform root-cause analysis on data and integrations.
• Experience with AI/ML data preparation, preprocessing, feature engineering, and model deployment.
• Familiarity with vector databases, embeddings, and RAG-based applications.
• Strong communication skills and ability to collaborate across teams.
• Ability to handle confidential and sensitive information responsibly.

Technologies

• Data & BI: SQL Server, T-SQL, SSIS/SSRS, ETL/ELT, Power BI, DAX, PowerQuery
• Programming: Python, R, C++, Julia, JavaScript, SQL
• File Formats: JSON, XML, SQL
• Extras (Nice to Have): PowerShell, Regex, VBA, documentation/process mapping, Tableau/Domo, Azure ML, legal tech platforms, LLM integration (OpenAI, Azure OpenAI, Claude), embedding models

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