Data Consultant

Particle41

$100K — $120K *
US-AnywhereRemote in United States
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related field.
  • 3+ years of proven experience in Data Engineering.
  • Proficiency in Python programming language.
  • Experience with SQL (MySQL, PostgreSQL) and NoSQL (MongoDB) databases.
  • Strong understanding of data warehousing/lakehouse principles and associated technologies.

Responsibilities

  • Design and maintain scalable ETL pipelines for processing large data volumes.
  • Build and optimize data storage solutions to ensure efficient data retrieval.
  • Integrate structured and unstructured data from multiple sources into a unified view.
  • Ensure data accuracy, consistency, and completeness through validation and cleansing processes.
  • Collaborate with stakeholders to gather technical requirements and provide insights.

Benefits

  • Supportive and dynamic work environment with opportunities for professional growth.
  • Commitment to diversity and inclusion in hiring and team culture.
  • Focus on continuous learning and innovation in technology and practices.
Full Job Description
Data Consultant

As a Data Consultant, 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 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.

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