Data Consultant

Summary

Particle41 is seeking a talented and versatile Data Consultant to support clients' data needs. The role focuses on designing, building, and maintaining scalable data pipelines and infrastructure, while collaborating with cross-functional teams on requirements gathering, Agile delivery, testing, debugging, and continuous improvement.

Responsibilities

• 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
• 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
• 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
• 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
• 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
• 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

• Bachelor's degree in Computer Science, Engineering, or related field
• Proven experience as a Data Engineering, with over 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 adapt to new ETL/ELT tools across various cloud providers
• Familiarity with version control systems like Git and collaborative development workflows
• Competence in working on Linux OS and creating shell scripts
• Solid understanding of software engineering principles, design patterns, and best practices
• 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

Qualifications

Must Haves

• Bachelor's degree in Computer Science, Engineering, or related field
• Proven experience as a Data Engineering, with over 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 adapt to new ETL/ELT tools across various cloud providers
• Familiarity with version control systems like Git and collaborative development workflows
• Competence in working on Linux OS and creating shell scripts
• Solid understanding of software engineering principles, design patterns, and best practices
• 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