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Particle41

Provides expert application, DevOps, ML teams

Data Engineer - Tableau

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in ArgentinaNo salary listedRemote

About the Job

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • At least 3 years of experience as a Data Engineer.
  • Strong proficiency in Python.
  • Experience with SQL databases, including MySQL and PostgreSQL, and NoSQL databases, including MongoDB.
  • 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 machine learning and artificial intelligence 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.
  • Comfort working in Linux and writing shell scripts.
  • Familiarity with Git and collaborative development workflows.
  • Strong communication skills and ability to work across technical and non-technical teams.

Responsibilities

  • Design, develop, and maintain scalable ETL/ELT pipelines to process large volumes of data from diverse sources.
  • Build and optimize data lakes and data warehouses for efficient data 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.
  • 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, including 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 tools such as matplotlib, seaborn, and plotly, or similar tools.
  • Support AI/ML workflows by building and maintaining data pipelines for 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, including copilots, intelligent search, and automated reporting, by ensuring clean, well-structured upstream data.
  • Contribute to prompt engineering and evaluation frameworks where data context is a key input.
  • 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.
  • Participate in sprint planning, stand-ups, and sprint reviews.
  • Deliver solutions on time and within scope, adapting when priorities shift.
  • Write unit and integration tests to validate pipeline reliability and data accuracy.
  • Identify and resolve defects, performance bottlenecks, and data quality issues.
  • Stay current with cloud platforms and emerging data engineering tools.
  • Propose solutions to improve performance, security, and scalability.

About the Company

Particle41

Provides expert application, DevOps, ML teams

Particle41 builds expert teams across software development, DevOps, and machine learning to strengthen a client’s capabilities. It assembles cross-functional teams that integrate into client projects, guiding work with clear communication and predictable timelines to drive fast progress. The service emphasizes specialized, high-caliber teams that augment the client’s own capabilities with speed, transparency, and forward planning. Its goal is to amplify a client’s business by delivering dependable teams that advance critical development, operations, and ML initiatives.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Frisco, TX
Founded
2015

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