[All remote jobs](https://jobicy.com/jobs.md)[![Particle41 logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/11/06a9d08339e9-221.webp)](https://jobicy.com/company/particle41.md)[Particle41](https://jobicy.com/company/particle41.md) # Data Engineer (Tableau) AI Summary Particle41 is hiring a Data Engineer to build scalable ETL/ELT pipelines, data platforms, and Tableau-based reporting solutions. The role spans data ingestion, transformation, quality validation, warehousing, lakehouse practices, and client-facing dashboards. It also supports AI and ML workflows through feature engineering, vector-store integration, and reliable training and inference data pipelines. The engineer will collaborate with product managers and stakeholders in Agile delivery while testing, debugging, documenting, and optimizing data systems. Strong Python, SQL, Tableau, cloud data-stack, and distributed-processing experience are central to success.[Apply for this job](#job-application)[View company](https://jobicy.com/company/particle41.md)ShareRemote from[Argentina](https://jobicy.com/job-region/argentina.md)SalaryUndisclosedDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceOpen levelPublished11 Nov 2026Apply before11 Dec 2026Listing views28Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. Data Engineer [Particle41](https://jobicy.com/company/particle41.md) 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. * Strong communication skills and the ability to work across technical and non-technical teams. ### About Particle41 Our core values of Empowering, Leadership, Innovation, Teamwork, and Excellence drive everything we do — ELITE. E — Empowering: Enabling individuals to reach their full potential L — Leadership: Taking initiative and guiding each other toward success I — Innovation: Embracing creativity and new ideas to stay ahead T — Teamwork: Collaborating with empathy to achieve common goals E — Excellence: Striving for the highest quality in everything we do Particle41 welcomes individuals from all backgrounds committed to our mission and values. We provide equal employment opportunities to all employees and applicants. Hiring and employment decisions are based on merit and qualifications — without discrimination based on race, color, religion, caste, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, local, or international laws. For assistance during the application or interview process, contact us at careers@Particle41.com Show more [Apply now >](https://jobicy.com/jobs/161424-data-engineer-tableau.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a broad mid-level data engineering role requiring practical capability across pipelines, databases, Tableau, cloud platforms, and AI/ML data infrastructure. The combination of client-facing visualization work and production engineering increases the technical and stakeholder-management complexity. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$55,000US market range (per year)$45k–$70k0$77k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer compensation was disclosed. The annual figures are estimated USD market guidance for a mid-level remote Data Engineer based in Argentina with Tableau, cloud data engineering, and AI/ML pipeline responsibilities; the yearly period is inferred from the full-time professional role. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Tableau](https://jobicy.com/jobs?search_keywords=Tableau.md)[ETL/ELT Pipelines](https://jobicy.com/jobs?search_keywords=ETLELT%20Pipelines.md)[Data Warehousing](https://jobicy.com/jobs?search_keywords=Data%20Warehousing.md)[Data Lakes](https://jobicy.com/jobs?search_keywords=Data%20Lakes.md)[Databricks](https://jobicy.com/jobs?search_keywords=Databricks.md)[Apache Spark](https://jobicy.com/jobs?search_keywords=Apache%20Spark.md)[PySpark](https://jobicy.com/jobs?search_keywords=PySpark.md)[Data Modeling](https://jobicy.com/jobs?search_keywords=Data%20Modeling.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Azure](https://jobicy.com/jobs?search_keywords=Azure.md)[GCP](https://jobicy.com/jobs?search_keywords=GCP.md)[Machine Learning Data Pipelines](https://jobicy.com/jobs?search_keywords=Machine%20Learning%20Data%20Pipelines.md)[Data Quality](https://jobicy.com/jobs?search_keywords=Data%20Quality.md) Sample interview questionsHow would you design an ETL/ELT pipeline that ingests data from multiple structured and unstructured sources?I would begin by defining source contracts, schemas, refresh requirements, data ownership, and quality rules. I would separate ingestion, transformation, validation, and serving layers, using orchestration, idempotent processing, logging, retry handling, and metadata tracking. I would land raw data in durable storage, transform it into governed analytical models, and add automated tests for freshness, completeness, and reconciliation. What steps do you take to improve Tableau dashboard performance? I first identify whether the bottleneck is in the data source, extract, calculations, workbook design, or network connection. Typical improvements include using extracts where appropriate, optimizing SQL and data models, reducing high-cardinality fields, limiting unnecessary marks, simplifying calculations, and using context filters selectively. I also validate performance with representative user interactions and document the trade-offs between live data and speed. Describe your approach to ensuring data quality in a production pipeline. I implement quality controls at each stage, including schema validation, null and uniqueness checks, range checks, referential-integrity checks, and source-to-target reconciliation. I define alert thresholds and route failures to observable logs and dashboards so issues can be investigated quickly. I also work with stakeholders to establish clear definitions for business metrics and acceptable data-quality standards. How have you supported machine learning or LLM-related data workflows? I focus on creating reproducible, versioned data pipelines for training, evaluation, and inference. This can include feature engineering, dataset validation, tokenization workflows, embedding generation, vector-store ingestion, and lineage tracking. I ensure that sensitive data is handled appropriately and that model inputs remain consistent across development and production environments. How would you translate a stakeholder's reporting request into a Tableau solution? I would clarify the business decision the report needs to support, the target users, required metrics, dimensions, refresh cadence, and expected interactions. Then I would validate source availability, design the data model and dashboard wireframe, and confirm metric definitions before building. I would review an initial version with stakeholders, incorporate feedback, and provide documentation so users understand the dashboard's scope and limitations. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. Keep exploring ## Related remote jobs. * ![Deepgram logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2020/12/WRILS-201212160008-406229.jpg) Deepgram Nov 11 New ### [Marketing & GTM Data Analyst](https://jobicy.com/jobs/161415-marketing-gtm-data-analyst.md) Company Overview Deepgram is bringing the world’s most natural interface, voice, to the technology we use every day. 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