Data & ML Engineer
Confirmed on the employer's own hiring board on Oct 1, 2026. First seen by Alion on Oct 1, 2026. Job Mail scores D on the Alion truth index.
Responsibilities:
Pipeline Design: Build and maintain modular, reusable ingestion and orchestration (APIs, SQL stored procedures, ETL/ELT) connecting sources such as CAMs, ERP, OT/IoT, and SharePoint into the SSOT.
Modeling & Optimization: Design coherent data models and feature pipelines supporting analytics and ML; execute advanced SQL performance and index tuning.
Operations: Maintain domain operational health, including active monitoring, alerting, performance tuning, and incident resolution.
Model Development: Build, evaluate, and integrate ML algorithms (forecasting, anomaly detection, neural networks) into active data workflows using standard Python libraries.
MLOps Implementation: Manage data/model versioning, CI/CD, drift monitoring, overfitting controls, and automated retraining pipelines for owned use cases.
Platform Configuration: Own AVEVA PI and CAMs for assigned sites/domains, designing Asset Framework (AF) element templates, hierarchies, event frames, and notifications.
Lifecycle Management: Oversee asset onboarding/offboarding, ensuring proper registration, interface maintenance, and data alignment with SSOT dashboards.
Standards & Security: Enforce data governance, IT security standards, and structured change management (approvals and rollback procedures).
Architectural Decisions: Autonomously make scalable design choices for owned domains, seeking alignment on major structural decisions.
Communication: Translate complex technical decisions and trade-offs for non-technical business stakeholders.
Mentorship & Delivery: Review peer code, mentor associates, drive cross-divisional alignment to meet timelines, and introduce new ML/data capabilities to the team.
Minimum Requirements:
Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related quantitative field.
Experience: 5-7 years in data engineering or platform development (5+ years acceptable with a demonstrated track record of independent delivery ownership).
Technical Experience: Hands-on experience with API integrations, ETL/ELT orchestration, data modeling, production operations, and deploying ML models.
Skills & Competencies
Programming & Querying: Strong Python and advanced SQL (schema design, index tuning, performance optimization). C# is an advantage.
Data & ML Engineering: Proven ability to build end-to-end ingestion frameworks, data models, and feature pipelines alongside solid MLOps discipline.
Industrial Platforms: Practical experience managing AVEVA PI (AF modeling, interfaces, event frames) and CAMs.
Core Behaviors: High degree of self-direction, strong engineering discipline, and clear stakeholder communication skills.
Advantageous
OT / Industrial Integration: Direct configuration of AVEVA PI tools (e.g., PI Integrator, APIs) and hands-on experience with energy/industrial IoT data.
Advanced ML: Production experience with MLOps frameworks and deep learning libraries (TensorFlow, PyTorch).
Cloud & Big Data: Experience with data lake architectures and orchestration tools (Azure Data Factory, Airflow, or Prefect).
Low-Code Automation: Working knowledge of Power Apps and Power Automate.
Benefits:
Competitive salary based on experience (salary can potentially be more based on experience/skills)
IF you meet the above requirements and want to make a career-changing move, apply today by emailing your CV to [email protected]