Sr. Data Engineer - AI

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 Type Script, 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 Type Script, 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

Job Requirements

Minimum Requirements:

Education and Experience Undergraduate degree in Computer Science, Data Engineering, Information Systems, or related field8+ 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 Type Script or JavaScript, preferably with Vue and Quasar, including component-based design and API integration

Strong knowledge of relational and No

SQL 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 Type Script or JavaScript, preferably Vue and Quasar, with reusable…