Data Engineer (Tableau)

Data Engineer

Particle41 is seeking a talented Data Engineer to join our team. You will design, build, and maintain data pipelines and infrastructure, support client-facing data visualization, and contribute to AI-assisted data workflows. You will work across the full data lifecycle — from raw ingestion to polished, decision-ready output — in collaboration with cross-functional teams.

In This Role You Will

Software Development

• Design, develop, and maintain scalable ETL/ELT pipelines to process large volumes of data from diverse sources.
• Build and optimize data storage solutions — data lakes and data warehouses — for efficient retrieval and processing.
• Integrate structured and unstructured data from internal and external systems into a unified view for analysis.
• Ensure data accuracy, consistency, and completeness through validation, cleansing, and transformation.
• Maintain clear documentation for data processes, tools, and systems.

Data Visualization

• Build and maintain Tableau dashboards and reports that translate complex datasets into clear, decision-ready visuals.
• Design data models and extracts optimized for Tableau performance, including live connections and published data sources.
• Apply data visualization best practices — chart selection, layout, color, and interactivity — to produce client-ready output.
• Partner with stakeholders to understand reporting needs and translate them into visual solutions.
• Support ad hoc analysis using Tableau, Python-based charting (matplotlib, seaborn, plotly), or similar tools.

AI and Data Support

• Support AI/ML workflows by building and maintaining the data pipelines that feed model training, inference, and evaluation.
• Assist with data preparation for LLM and machine learning projects, including feature engineering, tokenization pipelines, and vector store integration.
• Help teams adopt AI-assisted data tooling — copilots, intelligent search, automated reporting — by ensuring clean, well-structured data is available upstream.
• Contribute to prompt engineering and evaluation frameworks where data context is a key input.

Requirements Gathering and Analysis

• Work with product managers and stakeholders to gather requirements and translate them into technical solutions.
• Provide technical input during requirements sessions to align data capabilities with business needs.

Agile Development

• Participate in sprint planning, stand-ups, and sprint reviews.
• Deliver solutions on time and within scope. Adapt when priorities shift.

Testing and Debugging

• Write unit and integration tests to validate pipeline reliability and data accuracy.
• Identify and resolve defects, performance bottlenecks, and data quality issues.

Continuous Learning

• Stay current with cloud platforms (AWS, Azure, GCP) and emerging data engineering tools.
• Propose solutions to improve performance, security, and scalability.

Skills and Experience We Value

• Bachelor’s degree in Computer Science, Engineering, or a related field.