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.
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.
