A Junior Data Engineer is responsible for supporting the design, development, and maintenance of data pipelines to ensure reliable data flow for analytics and reporting. The role involves tasks such as cleaning, validating, and integrating data, as well as assisting with data storage solutions under the guidance of senior engineers. Core responsibilities include writing SQL and Python scripts for data processing, contributing to database management, collaborating on cloud platforms such as Snowflake and AWS, and documenting data workflows. Candidates should have a solid foundation in data engineering concepts, software engineering practices, and basic cloud computing, combined with strong communication and problem-solving skills.
Key Responsibilities:-
Data Pipeline Development: Design, build, and maintain data pipelines for collecting, processing, and integrating data from various sources.
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Data Cleaning and Validation: Perform data cleaning and validation to ensure data quality and integrity, addressing missing values and duplicate entries.
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Database Management: Assist with database schema design, data modeling, and database optimization to ensure efficient data storage and retrieval.
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ETL Processes: Implement and support ETL (Extract, Transform, Load) processes to move data from source systems to data warehouses or data lakes.
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Collaboration: Work closely with data scientists, senior engineers, and other stakeholders to understand requirements and build scalable data infrastructure.
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Documentation: Create and maintain documentation for data pipelines, data models, and data processes.
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Tooling: Gain hands-on experience with big data technologies, cloud platforms (e.g., AWS, Azure, GCP, Snowflake).
Education, Experience & Skills:-
Proficiency in Python and SQL for effective data manipulation and querying.
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Solid understanding of relational databases (e.g., PostgreSQL, MySQL) and core data modeling concepts.
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Basic familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud Platform (GCP).
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Experience working with big data tools and frameworks, including Snowflake.
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Foundational knowledge of data engineering principles and exposure to Agile methodologies.
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Awareness of data governance, security, and quality management practices.
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Collaboration: Ability to work effectively as part of cross-functional and diverse teams.
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Communication: Strong verbal and written skills to clearly convey ideas to both technical and non-technical stakeholders.
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Problem-Solving: Analytical mindset with the ability to troubleshoot and resolve technical challenges.
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Adaptability: Quick learner who can embrace new technologies and adjust to evolving business needs.
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This is a remote position, but the candidate must reside in the United States.
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