Data Engineer Role: AI Pipelines & Tableau | Particle41 in Columbus
Career & Market Insight
Career Development Potential: This role sits at a high-demand intersection of data engineering, AI/ML pipeline support, and data visualization — a combination that is increasingly valued as companies build LLM-powered products. Skills in Tableau, PySpark, vector databases, and feature engineering are all in strong market demand heading into 2025-2026.
Compensation Context: No salary is listed, which is a yellow flag. For a mid-level Data Engineer (3+ years) in Argentina, market rates for US-facing remote roles typically range from $3,000–$6,000/month USD depending on the company and stack complexity. Globally, this profile commands $90,000–$130,000 USD annually in US markets. Negotiate accordingly and confirm the compensation structure (USD vs. ARS).
Green Flags:
- Exposure to LLM pipelines, vector stores, and prompt engineering is cutting-edge and future-proof.
- Client-facing visualization work builds a portfolio of business impact, not just backend plumbing.
- Agile environment signals structured delivery culture — good for career progression tracking.
Yellow Flags:
- No salary disclosed; benefits are not listed — negotiate proactively.
- The breadth of required skills (ETL, Tableau, ML pipelines, ELK, Redis) suggests a generalist "do it all" expectation, which can be rewarding but also demanding in a consulting/agency context like Particle41.
Overall, this is a strong mid-career move for engineers wanting AI/data crossover experience in a consulting environment that exposes you to diverse client stacks.
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.
- 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 [email protected]
Frequently Asked Questions
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