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
