Data Engineer
Data Engineer
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 This Role, You Will: Software Development
- Design, develop, and maintain scalable ETL (Extract, Transform, Load) pipelines to process large volumes of data from diverse sources.
- Build and optimize data storage solutions, such as data lakes and data warehouses, to ensure efficient data retrieval and processing.
- 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.
Requirements Gathering and Analysis
- Collaborate with product managers, and other stakeholders to gather requirements and translate them into technical solutions.
- Participate in requirement analysis sessions to understand business needs and user requirements.
- Provide technical insights and recommendations during the requirements-gathering process.
Agile Development
- Participate in Agile development processes, including sprint planning, daily stand-ups, and sprint reviews.
- Work closely with Agile teams to deliver software solutions on time and within scope.
- Adapt to changing priorities and requirements in a fast-paced Agile environment.
Testing and Debugging
- Conduct thorough testing and debugging to ensure the reliability, security, and performance of applications.
- Write unit tests and validate the functionality of developed features and individual elements.
- Writing integration tests to ensure different elements within a given application function as intended and meet desired requirements.
- Identify and resolve software defects, code smells, and performance bottlenecks.
Continuous Learning and Innovation
- Stay updated with the latest technologies and trends in full-stack development.
- Propose innovative solutions to improve the performance, security, scalability, and maintainability of applications.
- Continuously seek opportunities to optimize and refactor existing codebase for better efficiency.
- Stay up to date with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Collaboration
- Collaborate effectively with cross-functional teams, including testers, and product managers.
- Foster a collaborative and inclusive work environment where ideas are shared and valued.
Skills and Experience We Value:
- 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 Python programming language.
- 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, datawarehousing/lakehouse, principles, database and ORM, data analysis databricks, panda's, Spark, Pyspark, Machine learning, OpenCV, scikit-learn.
- Utilities & Tools: logging, requests, subprocess, regex, pytest
- ELK stack, Redis, distributed task queues
- Strong understanding of data warehousing/lakehousing principles and concurrent/parallel processing concepts.
- Familiarity with at least one cloud data engineering stack (Azure, AWS, or GCP) and the ability to quickly learn and ad