Sr. Data Engineer - AI

dfa; Kansas City (KS); On-site; USD 140,000 - 180,000; Full time

Job summary

dfa in Kansas City seeks a senior data engineer to design, build, and support secure, scalable data pipelines connecting enterprise data sources to AI/ML models. You will ensure data accuracy, governance, and reliable delivery while enabling AI-enabled applications with frontend support using TypeScript, JavaScript, Vue, and Quasar.

Collaborate with software engineers, data architects, and product teams to align data solutions with model requirements and enterprise standards.

Qualifications

• Undergraduate degree in Computer Science, Data Engineering, Information Systems, or related field.
• 8+ years data engineering, software development, or related experience, including data pipelines for AI/ML systems.
• Proficiency with Python, SQL, PySpark, Snowflake, Databricks, and Apache Airflow.
• Experience developing or supporting modern SPAs using TypeScript/JavaScript, preferably Vue and Quasar, with API integration.
• Strong knowledge of relational/NoSQL databases, data warehouses or lakes, Azure Data Factory, and Kafka.
• Experience with at least one cloud data ecosystem (prefer Azure) and IaC/CI/CD practices.
• Certifications in cloud data engineering or data privacy/security and experience with MLOps preferred.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines for AI/ML data
• Ensure data accuracy, currency, reliability, and security with cleansing, validation, and monitoring
• Troubleshoot complex integration and performance issues, remove bottlenecks, apply caching and distributed processing
• Own AI data infrastructure components with monitoring, logging, data lineage, and quality metrics
• Apply enterprise architecture, AI governance, privacy, security, coding, and CI/CD standards; communicate risks to leadership

Skills

Data engineering

AI/ML pipelines

ETL/ELT design

Troubleshooting

Cross-team collaboration

APIs integration

Cloud data ecosystems

English communication

Education

Bachelor's degree in CS/Data Eng/IS

Tools

Python

SQL

PySpark

Snowflake

Databricks

Apache Airflow

Azure Data Factory

Kafka

TypeScript

JavaScript

Vue

Quasar

Job description

Serve in a senior-level technical role designing, building, and supporting secure, scalable data pipelines that connect enterprise data sources to AI/ML models. Ensure data is accurate, current, compliant, and aligned with enterprise AI governance standards while independently solving complex integration challenges and advancing data engineering best practices. Provide practical front-end development support using TypeScript, JavaScript, Vue, and Quasar to help deliver intuitive AI-enabled applications.

Job Duties and Responsibilities:

• Design, build, and optimize scalable ETL/ELT pipelines that ingest, transform, and integrate structured and unstructured enterprise data for AI/ML model training and inference
• Ensure data is accurate, current, reliable, and secure through cleansing, normalization, validation, automation, continuous updates, monitoring, and error handling
• Troubleshoot complex integration and performance issues, remove bottlenecks, and apply appropriate techniques such as caching, distributed processing, and specialized ETL patterns
• Own key AI data infrastructure components and ensure they are scalable, maintainable, and supported by effective monitoring, logging, documentation, data lineage, and quality metrics
• Apply enterprise architecture, AI governance, privacy, security, coding, and CI/CD standards to data solutions and communicate risks or limitations to leadership
• Partner with Software engineers, data architects, domain experts, product teams, and platform teams to align data solutions with model requirements, business goals, and enterprise standards
• Develop and support front-end components for AI-enabled applications using TypeScript, JavaScript, Vue, and Quasar to deliver intuitive, maintainable user experiences
• Independently deliver assigned work, influence cross-team decisions, promote data engineering best practices, and evaluate technologies that improve AI data delivery
• The requirements herein describe the general nature and level of work performed by the employee but are not a complete list of responsibilities, duties, and skills required. Other duties may be assigned as needed

Minimum Requirements:

Education and Experience

• Undergraduate degree in Computer Science, Data Engineering, Information Systems, or related field
• 8+ years data engineering, software development, or related experience, including work on data pipelines for AI/ML systems
• Proficiency with data engineering languages, platforms, and orchestration tools such as Python, SQL, PySpark, Snowflake, Databricks, and Apache Airflow
• Experience developing or supporting modern single-page applications using TypeScript or JavaScript, preferably with Vue and Quasar, including component-based design and API integration
• Strong knowledge of relational and NoSQL databases, data warehouses or data lakes, integration platforms such as Azure Data Factory, and streaming technologies such as Kafka
• Experience with at least one major cloud data ecosystem, preferably Azure, and familiarity with infrastructure-as-code and automated deployment practices
• Proven ability to design and implement ETL/ELT pipelines, manage databases or data lakes, and integrate large-scale data systems
• Certifications in cloud data engineering or in data privacy/security and experience with MLOps or AI/ML lifecycle management preferred

Knowledge, Skills and Abilities

• Must be willing to travel 15-25% (1-2 times per quarter)
• Deep knowledge of data engineering and AI/ML pipeline practices, including the ability to design and optimize scalable, reliable, and efficient data solutions
• Strong understanding of data quality, governance, privacy, security, and regulatory requirements
• Able to independently analyze and troubleshoot complex data and integration issues and apply creative, data-driven solutions when standard approaches are insufficient
• Able to align technical solutions with business priorities, including speed, cost, risk, reliability, and desired outcomes, and exercise sound judgment in situations with limited precedent
• Able to communicate complex technical concepts clearly, collaborate across teams, and build stakeholder trust through transparency and reliable delivery
• Able to lead technical initiatives, document approaches clearly, influence peers, and promote adoption of standards and best practices
• Practical ability to develop and support accessible, responsive single-page applications using TypeScript or JavaScript, preferably Vue and Quasar, with reusable components and API integration
• Must be able to read, write, and speak English

An Equal Opportunity Employer including Disabled/Veterans