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. - 3+ years of experience as a Data Engineer. - Strong Python proficiency. - Experience with SQL (MySQL, PostgreSQL) and NoSQL (MongoDB) databases. - Hands-on experience with Tableau — dashboard development, data source management, and performance optimization. - Familiarity with data warehousing and lakehouse principles; experience with Databricks, Spark, PySpark, and pandas. - Experience building or supporting ML/AI data pipelines, including feature stores, vector databases, or model serving infrastructure. - Familiarity with at least one cloud data stack (Azure, AWS, or GCP). - Working knowledge of the ELK stack, Redis, and distributed task queues. - Proficiency with Python libraries including Flask, scikit-learn, requests, pytest, and logging utilities. - Comfortable working in Linux and writing shell scripts. - Familiarity with Git and collaborative development workflows.

📌 Data Engineer (Tableau) (Argentina)
🏢 Particle41
📍 Argentina