SQL AI Jobs

Discover the latest remote and onsite SQL AI roles across top active AI companies. Updated hourly.

Check out 153 new SQL AI roles opportunities posted on The Homebase

Senior Data Engineer, People Analytics

New
Top rated
Crusoe
Full-time
Full-time
Posted

Build and maintain resilient ETL pipelines to centralize data from core HCM and ATS systems into Google Cloud Platform, Big Query, and other people analytics products. Architect a semantic data layer using dbt to translate raw database schemas into business-friendly logic, enabling non-technical leaders to ask natural language questions and get accurate answers. Leverage AI and LLMs to extract insights from unstructured data and build predictive models for attrition and headcount planning. Design data products that solve operational problems by automating HR workflows, building custom apps for internal mobility, or redesigning organizational structure. Partner with Talent, Finance, and People leaders to translate business questions into data inquiries and consult on analytics possibilities. Design and deploy Sigma workbooks to guide executives through complex narratives to ensure data-driven action.

$165,000 – $200,000
Undisclosed
YEAR

(USD)

Denver, United States
Maybe global
Onsite
Python
Google Cloud Platform
SQL
Data Pipelines
AI

Marketing Intern - Singapore

New
Top rated
Dataiku
Intern
Full-time
Posted

Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help customers achieve success. Scope and co-develop production-level data science projects with customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

Undisclosed

()

Singapore
Maybe global
Hybrid
Python
JavaScript
SQL
PyTorch
Spark

Marketing Intern - Seoul

New
Top rated
Dataiku
Intern
Full-time
Posted

Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help our customers achieve success. Scope and co-develop production-level data science projects with our customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

Undisclosed

()

Seoul, South Korea
Maybe global
Hybrid
Python
JavaScript
SQL
PySpark
Machine Learning

Marketing Intern - Tokyo

New
Top rated
Dataiku
Intern
Full-time
Posted

Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help our customers achieve success. Scope and co-develop production-level data science projects with our customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

Undisclosed

()

Tokyo, Japan
Maybe global
Hybrid
Python
JavaScript
SQL
PyTorch
Spark

Software Engineer, Data & Retrieval

New
Top rated
BenchSci
Full-time
Full-time
Posted

The Software Engineer is responsible for utilizing the Agent Development Kit (ADK) to design, develop, and deploy autonomous agents and "skills" capable of multi-step data retrieval tasks. They design and develop backend systems and APIs to expose bioinformatics data and implement advanced search and retrieval mechanisms to provide LLMs with up-to-date grounded information. Their duties include tuning storage technologies, creating high-performance query plans, designing solutions, and adapting existing approaches to solve issues within web app architecture and interfaces. They operationalize production-grade data pipelines using processing engines like Apache Beam, collaborate with other engineers to address document extraction, enrichment, and retrieval challenges, and model scientific experiments from unstructured data. The engineer also troubleshoots and resolves production issues promptly, ensures code is testable, self-documenting, and reliable, communicates decisions to impacted teams, works on client-facing projects with large pharmaceutical companies, and balances independent work with collaborative efforts for complex architectural changes.

$100,000 – $140,000
Undisclosed
YEAR

(USD)

Toronto, Canada
Maybe global
Hybrid
Python
SQL
API Development
GCP
Data Pipelines

ML Systems Engineer (Platform & Biometrics Data Infrastructure)

New
Top rated
Eight Sleep
Full-time
Full-time
Posted

Build and operate high-throughput pipelines for sensor and event data (batch and streaming) ensuring quality, lineage, and reliability. Create scalable dataset curation and labeling workflows including sampling, slice definitions, weak supervision, gold-set management, and evaluation set integrity. Develop ML platform components such as feature pipelines, training orchestration, model registry, reproducible experiment tracking, and automated evaluation. Implement monitoring and observability for production ML systems covering data drift, performance regression, alerting, and automated failure detection. Standardize schemas and interfaces across studies and product telemetry to enable reusable, consistent analytics and model development. Collaborate cross-functionally with ML engineers, data science, firmware, and backend teams to support new studies and product launches, ensuring data architecture meets evolving research and product needs.

Undisclosed

()

San Francisco, United States
Maybe global
Onsite
Python
SQL
MLOps
Docker
Kubernetes

Data Integration Lead | R&D

New
Top rated
nexos.ai
Full-time
Full-time
Posted

Lead a team of 5-6 engineers to ensure all services, platforms, and teams within the SaaS product have accurate and up-to-date scorecards that provide actionable insights and support continuous improvement. Build and maintain reliable processes to keep platform and service inventory data accurate and current. Provide technical leadership and mentorship to engineers through complex system design decisions and drive technical excellence. Architect and implement a self-improving and self-healing data processing model, large-scale, reliable data pipelines, and AI/ML-enabled systems ensuring high performance, scalability, and data quality. Lead the development of data warehousing and analytics solutions such as BigQuery or Snowflake. Collaborate with stakeholders to translate business needs into scalable data and ML solutions while operating effectively in a fast-paced environment. Promote scorecard usage across the organization via workshops, manuals, and internal communications.

€5,500 – €8,200 / month
Undisclosed
MONTH

(EUR)

Vilnius, Lithuania
Maybe global
Onsite
Python
Data Pipelines
MLOps
MLflow
SQL

Senior Data Scientist, Marketing

New
Top rated
Harvey
Full-time
Full-time
Posted

The Senior Marketing Data Scientist will partner closely with Harvey’s Marketing organization to build the marketing data science function from the ground up. Responsibilities include embedding deeply with the Marketing organization as a trusted partner to identify opportunities to improve performance and drive growth, defining, tracking, and evolving core metrics across marketing and business functions, and building scalable dashboards and reporting frameworks that enable data-driven decision-making. The role involves designing, implementing, and evaluating models such as multi-touch attribution, marketing mix modeling, and incrementality for comprehensive Marketing Channel and Campaign performance and contribution. The Senior Data Scientist will apply statistical and machine learning techniques to model user behavior, forecast trends, and identify opportunities for growth and optimization. They will translate complex analyses into compelling stories with clear recommendations for cross-functional partners and executives, partner with Marketing, RevOps, and GTM Systems to co-develop data infrastructure ensuring robust pipelines, reliable data sources, and scalable systems to power analytics and modeling. The role also includes leading cross-functional analytics initiatives to synthesize competitive dynamics, customer feedback, and market trends into actionable business opportunities and championing a data-informed culture by establishing best practices, mentoring peers, and shaping the strategic role of data science at Harvey.

$170,000 – $200,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite
Python
SQL
Pandas
Machine Learning
Data Pipelines

Senior Engagement Manager

New
Top rated
Dataiku
Full-time
Full-time
Posted

Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help customers achieve success. Scope and co-develop production-level data science projects with customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

Undisclosed

()

Singapore
Maybe global
Hybrid
Python
JavaScript
SQL
PyTorch
Spark

Infrastructure Engineer

New
Top rated
Dataiku
Full-time
Full-time
Posted

Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help our customers achieve success. Scope and co-develop production-level data science projects with our customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

Undisclosed

()

Paris or Berlin or London, France, Germany, Netherlands or United Kingdom
Maybe global
Hybrid
Python
JavaScript
SQL
MLOps
Docker

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[{"question":"What are SQL AI jobs?","answer":"SQL AI jobs combine database management with artificial intelligence. These positions involve creating systems that generate SQL queries from natural language, optimize database performance, build recommendation engines, and extract insights from data. Professionals in these roles might work on tools like AI2sql, Chat2DB, or Microsoft Copilot for Azure SQL, helping organizations access and analyze data more efficiently."},{"question":"What roles commonly require SQL skills?","answer":"Data Analysts use these skills to retrieve customer data and optimize slow-running queries. Database Administrators manage databases and resolve performance issues. Developers convert natural language requirements into queries. AI Engineers build data-driven applications requiring database connectivity. Even non-technical stakeholders benefit from AI-assisted tools that allow them to perform complex data operations without deep technical knowledge."},{"question":"What skills are typically required alongside SQL?","answer":"Professionals need familiarity with specific database platforms like PostgreSQL, MySQL, or Microsoft SQL Server. Query optimization knowledge is essential for improving performance. Understanding data structures, including categorical values and database schemas, complements core abilities. Database connectivity expertise helps manage data flows between applications and databases. Many employers now value natural language processing skills for AI-assisted query generation."},{"question":"What experience level do SQL AI jobs usually require?","answer":"Experience requirements vary widely based on the specific role. Entry-level positions might require basic database knowledge while emphasizing learning AI tools. Mid-level roles typically demand practical experience with query optimization and database design. Senior positions often require deep expertise in both database management and AI integration techniques. The emergence of AI-assisted tools has created opportunities for professionals with less technical SQL experience."},{"question":"What is the salary range for SQL AI jobs?","answer":"Salaries vary based on location, experience, industry, and specific role. Entry-level positions generally offer competitive compensation reflecting the specialized skill set. Mid-career professionals with proven expertise in both database management and AI integration command higher salaries. Senior roles combining deep technical knowledge with business acumen tend to be at the upper end of technology compensation scales."},{"question":"Are SQL AI jobs in demand?","answer":"These jobs show strong demand signals across multiple indicators. The growing ecosystem of AI-powered database tools demonstrates market interest. Major enterprises are integrating AI with database systems like Snowflake, BigQuery, and Azure SQL. Applications span diverse industries including finance, healthcare, retail, and government. The development of tools for both technical and non-technical users suggests expanding opportunities beyond traditional database specialists."},{"question":"What is the difference between SQL and NoSQL in AI roles?","answer":"In AI roles, structured query language excels at managing relational data with defined schemas, making it ideal for financial applications and traditional databases. NoSQL handles unstructured data better, supporting flexible schema designs for social media content and IoT applications. AI professionals may use relational databases when data relationships matter most, while choosing document-based systems when scalability and schema flexibility take priority."}]