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