Enterprise Data, Analytics & AI

Ketjen•Houston, TX

2d•Hybrid

About The Position

Are you ready to move your career forward and help shape our company’s and customers’ futures? If you aspire to challenge yourself, work with the best in the industry and join a successful team where you can make a meaningful contribution, then we invite you to join us at Ketjen Corporation, a provider of advanced catalyst solutions to leading producers in the petrochemical, refining, and specialty chemicals industries. Together, we can create a legacy marked by innovation, excitement, and energy. Ketjen is hiring for an Enterprise Data, Analytics & AI Manager. This position is hybrid , and located in Clear Lake, TX.

Requirements

8+ years in data engineering, analytics, or ML roles
3+ years leading technical data teams
Hands-on experience ML or AI systems
Track record of building enterprise-grade data platforms
Expert-level SQL and Python
Cloud platforms: Azure
Data warehousing: Databricks or equivalent
ML frameworks

Nice To Haves

Experience with LLMs, RAG pipelines, or generative AI in production environments
Familiarity with real-time streaming architectures (Kafka, Flink, Kinesis)
Relevant certifications: Databricks Certified

Responsibilities

Data Platform & Engineering Architect, build, and operate a scalable enterprise data platform (cloud-native).
Own the full data lifecycle: ingestion, transformation, storage, orchestration, and consumption layers
Establish and enforce data quality frameworks, SLA monitoring, and lineage tracking
Drive adoption of modern data stack tooling (dbt, Airflow, Spark, Kafka, Databricks, Snowflake, etc.)
Define and execute the enterprise AI/ML roadmap in collaboration with business stakeholders
Oversee the design, development, deployment, and monitoring of production AI/ML models
Evaluate and integrate large language models (LLMs) and generative AI capabilities into business workflows
Implement MLOps best practices including CI/CD for models.
Lead the development of self-service analytics capabilities, semantic layers, and BI infrastructure
Define KPIs, metrics frameworks, and executive reporting cadences
Championing a data-literate culture by delivering training, documentation, and stakeholder enablement
Hire, manage, and mentor a high-performing team
Own the enterprise master data governance program
Manage vendor relationships, licensing, and the data & AI budget
Communicate roadmaps, risks, and results clearly to stakeholders