EXECUTIVE - TECHNOLOGY (AI INTEGRATION - DATA ANALYST) (EG07)

Job Description

Job Purpose

Design, develop, and manage robust data pipelines and advanced analytics dashboards in support of Industry 4.0 initiatives

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Transform complex operational data into actionable intelligence, optimizing manufacturing processes, equipment reliability, and overall plant efficiency.

Drive digital transformation by championing data-driven decision-making, predictive analytics, and the strategic utilization of factory data assets.

Responsibilities

1. Data Collection and Ingestion - Collect, clean, and ingest production and process data from InfluxDB, SCADA historians, and other plant data sources.

2. Dashboard Development - Build, maintain, and enhance Grafana dashboards and operational reports for plant performance monitoring.

3. AI/ML Model Support - Assist in preparing data sets, feature engineering, and validating AI/ML model outputs under SM/M/AM direction.

4. Trend and Anomaly Analysis - Interrogate time-series production data; identify trends, anomalies, and performance deviations; present findings to the team.

5. Data Pipeline Maintenance - Maintain and monitor InfluxDB data ingestion pipelines, retention policies, and data quality checks.

6. Data Governance - Maintain data dictionaries, tag registers, and documentation for all data assets managed by the workstream.

7. Continuous Improvement Support - Identify data-driven improvement opportunities; support AM in translating findings into actionable engineering proposals.

8. Cross-Team Collaboration - Work with engineers and operations teams to understand data requirements; translate them into analytical solutions.

9. Standards and Security Compliance - Ensure all data handling activities comply with company data governance policies and IT/OT security requirements.

Qualification and Experience

1. Bachelor’s Degree in Data Science, Computer Science, Statistics, IT, or a related analytical field.

2. Minimum 1 year of experience in data analytics or data engineering, preferably within a manufacturing or continuous process environment.Fresh graduates welcome to apply.

3. High proficiency in data visualization and dashboard development tools (e.g., Grafana, Power BI, Tableau) or other data processing software (e.g., Knime)

4. Strong querying and database management skills, with experience in time-series databases (e.g., InfluxDB) and relational databases (SQL).

5. Familiarity with OT/IT data integration tools and flow-based programming (e.g., Node-RED) is a strong advantage.

6. Proven ability to translate complex, high-velocity technical data into clear, actionable business and operational insights.

7. Exposure to Python (Pandas, NumPy, Scikit-learn) for data processing and ML

8. Certification in data analytics, Python, or machine learning and any experience in industrial/manufacturing data is advantageous