Data Engineer — Azure ML, CI/CD & MLflow Specialist

Energy Innovation Corp; Carmel (IN); On-site; USD 93,000 - 122,000; Full time

Benefits offered by this job

Health coverage

Job summary

Community Development Partners is seeking a Data Engineer in Carmel, Indiana to switch between Plotly and Azure ML without losing momentum. The role blends a $93,000–$122,000 annual salary with autonomy to shape Statistical Modeling work in a collaborative team environment.

The candidate will lead design reviews, maintain CI/CD infrastructure across Indiana teams, and ensure dependencies are patched against CVEs, while driving MLflow improvements and Azure ML performance wins that impact

Qualifications

• Comfort defending a recommendation in front of skeptics.
• Growth mindset and openness to constructive feedback.
• Bias toward action with ability to wait when necessary.
• Diplomacy to align stakeholders with differing views.
• Eagerness to learn new skills and improve.
• Comfort being measured against a clear mid-level bar.

Responsibilities

• Lead Persuasion design reviews that catch costly mistakes before Carmel, IN builds them.
• Maintain and improve CI/CD infrastructure across IN engineering teams.
• Keep Community Development Partners's Persuasion dependencies patched before CVEs become incidents.
• Untangle the MLflow dependency knots that have slowed Carmel releases for months.
• Land Azure ML performance wins Community Development Partners can measure in retention numbers.

Skills

Communication advocacy

Growth mindset

Curiosity and action

Stakeholder diplomacy

Continuous learning

Performance-driven

Tools

Plotly

Azure ML

CI/CD

Job description

Community Development Partners is seeking a Data Engineer in Carmel, Indiana to switch between Plotly and Azure ML without losing momentum. The role blends a $93,000–$122,000 annual salary with autonomy to shape Statistical Modeling work in a collaborative team environment.

The candidate will lead design reviews, maintain CI/CD infrastructure across Indiana teams, and ensure dependencies are patched against CVEs, while driving MLflow improvements and Azure ML performance wins that impact