Here is a comprehensive, modern job description for a Junior Data Engineer that you can customize for your company's specific tech stack and culture.
Job Title: Junior Data Engineer
Department: Data & Analytics
Employment Type: Full-time
Location: [Insert Location - e.g., Remote / Hybrid / Onsite]
Experience Level: Entry to Mid-Level (1–2 years)
Position Overview
We are looking for a motivated and detail-oriented Junior Data Engineer to join our growing data team. In this role, you will help build, maintain, and optimize our data pipelines, ensuring that our data is clean, reliable, and easily accessible for data scientists, analysts, and business stakeholders.
This is an excellent opportunity for an aspiring data professional to work closely with senior engineers, gain hands-on experience with cutting-edge cloud data technologies, and directly impact our data-driven decision-making process.
Key Responsibilities
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Pipeline Development: Assist in designing, building, and maintaining robust Batch and Real-time ETL/ELT pipelines to ingest data from various sources (APIs, databases, third-party tools).
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Data Quality & Governance: Monitor data pipeline performance, troubleshoot data quality issues, and implement validation checks to ensure accurate data delivery.
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Database Management: Write, optimize, and maintain complex SQL queries, views, and schemas in our data warehouse.
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Collaboration: Partner with Data Analysts and Data Scientists to understand their data requirements and transform raw data into analytics-ready datasets.
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Documentation: Document data models, pipeline architectures, and data dictionaries to promote data literacy across the organization.
Required Skills & Qualifications
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Education: Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field (or equivalent practical experience/bootcamp background).
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SQL Proficiency: Strong foundational knowledge of SQL (writing joins, aggregations, and understanding query optimization).
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Programming: Solid coding skills in Python (preferred) or Java/Scala for data manipulation and scripting.
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Data Concepts: Understanding of fundamental data warehousing concepts, dimensional modeling (Star/Snowflake schemas), and ETL/ELT concepts.
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Problem-Solving: Strong analytical mindset with an eager desire to learn new technologies and methodologies.