Data Engineer (Elasticsearch + Data Warehousing) - Remote

Overview

Particle41 is seeking a talented and versatile Data Engineer to join our innovative team. As a Data Engineer, you will play a key role in designing, building, and maintaining robust data pipelines and infrastructure to support our clients' data needs. You will work on end-to-end data solutions, collaborating with cross-functional teams to ensure high-quality, scalable, and efficient data delivery. This is an exciting opportunity to contribute to impactful projects, solve complex data challenges, and grow your skills in a supportive and dynamic environment.

In Short

• Design, implement, and optimize Elasticsearch clusters for high-performance querying and data retrieval.
• Build and manage Elasticsearch indexes, ensuring data is stored, indexed, and queried efficiently.
• Build and optimize data storage solutions like data lakes and warehouses.
• Integrate structured and unstructured data from various internal and external systems to create a unified view for analysis.
• Ensure data accuracy, consistency, and completeness through rigorous validation, cleansing, and transformation processes.
• Maintain comprehensive documentation for data processes, tools, and systems while promoting best practices for efficient workflows.
• Collaborate with product managers and other stakeholders to gather requirements and translate them into technical solutions.
• Participate in Agile development processes, including sprint planning, daily stand-ups, and sprint reviews.
• Conduct thorough testing and debugging to ensure the reliability, security, and performance of applications.
• Stay updated with the latest technologies and trends in full-stack development.

Requirements

• Bachelor's degree in Computer Science, Engineering, or related field.
• Proven experience as a Data Engineer, with a minimum of 3 years of experience.
• Proficiency in Elasticsearch and Python programming language is a must.
• Experience with database technologies such as SQL (e.g., MySQL, PostgreSQL) and NoSQL (e.g., MongoDB) databases.
• Strong understanding of Programming Libraries/Frameworks and technologies such as Flask, API frameworks, Data warehousing/lakehouse, Principles, Database, ORM, Data analysis, Databricks, Pandas, Spark, PySpark, Machine learning, OpenCV, Scikit-learn.
• Familiarity with at least one cloud data engineering stack (Azure, AWS, or GCP) and the ability to quickly learn and adapt to new ETL/ELT tools across various cloud providers.
• Familiarity with version control systems like Git and collaborative development workflows.
• Excellent problem-solving and analytical skills, with a keen attention to detail.
• Effective communication skills, both written and verbal, and the ability to collaborate in a team environment.
• Adaptability and willingness to learn new technologies and tools as needed.

Benefits

• Opportunity to work on impactful projects.
• Supportive and dynamic work environment.
• Continuous learning and professional development.
• Collaborative team culture.
• Equal employment opportunities for all employees and applicants.