Data Engineer

Role details

Key responsibilities

• Design and maintain pipelines to ingest, clean and normalise structured and unstructured data.
• Build logic and confidence-scoring frameworks for trusted, conflict-free data records.
• Clean and validate data for uniformity, accuracy and consistency.
• Conduct exploratory data analysis and visualise trends and anomalies to guide preparation of data for AI solutions.
• Collaborate with AI Engineers and ML DevOps to deliver clean, well-attributed data to downstream models.
• Analyse AI agent usage across the business.

Technologies

• The role lists Python, R, SQL, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Plotly, Jupyter, dbt, Spark, Power BI, Git and REST APIs.

Core analytical skills

• Data wrangling, cleaning and normalisation for structured and unstructured data.
• Data validation, uniformity and feature engineering when needed.
• Entity resolution and deduplication; exploratory analysis and data quality assessment and monitoring.
• Clear technical documentation; Python proficiency.

Data visualisation and professional skills

• Design clear, insight-driven charts and graphs; present findings in pictorial and summary formats.
• Translate complex analysis into accessible visuals and build dashboards and reporting outputs.
• Communicate technical findings to non-technical audiences and collaborate with engineers, analysts and stakeholders.
• Use a structured, methodical approach to problem solving and be willing to ask questions and learn from feedback.

Nice to have

• Exposure to NLP or text classification.
• Familiarity with graph or semantic layers.
• Experience with cloud data platforms.
• Understanding of AI data governance principles.

About SCC

Benefits

• The posting mentions company benefits, a flexible benefits scheme, two paid volunteering days, career development and learning opportunities.