Job Description
Job Description
We are seeking a motivated and detail-oriented Junior Data Engineer to join our data team and help build, maintain, and improve the systems that collect, transform, store, and deliver data across the organization.
This is a full-time position offering $70,000–$90,000 per year, depending on experience, technical skills, education, and qualifications. Candidates with strong SQL and Python skills, relevant internships or project experience, and familiarity with cloud platforms or data pipelines may be considered toward the upper end of the compensation range.
The ideal candidate is eager to learn, enjoys solving technical problems, and wants to build a career in data engineering. You will work alongside experienced engineers and analysts while gaining hands-on experience with modern data technologies.
Key Responsibilities
- Assist in developing and maintaining ETL/ELT data pipelines.
- Collect, transform, validate, and prepare data from multiple sources.
- Write and optimize SQL queries for data extraction and transformation.
- Develop Python scripts and applications to automate data-processing tasks.
- Assist with maintaining databases, data warehouses, and data lakes.
- Monitor data pipelines and troubleshoot data-quality or processing issues.
- Perform data validation and testing to ensure accuracy and reliability.
- Support data integration projects involving APIs, applications, and third-party systems.
- Assist senior engineers with data modeling and database design.
- Document data pipelines, processes, and technical procedures.
- Participate in code reviews and follow software-development best practices.
- Work with data analysts, data scientists, software engineers, and business teams.
- Learn and apply cloud-based data engineering technologies.
- Identify opportunities to automate repetitive data-management processes.
Qualifications Required
- Bachelor's degree in Computer Science, Data Engineering, Information Technology, Mathematics, Engineering, or a related field, or equivalent practical experience.
- 0–2 years of experience in data engineering, software engineering, analytics engineering, or a related technical field.
- Working knowledge of SQL.
- Basic to intermediate proficiency in Python.
- Understanding of relational databases and data structures.
- Familiarity with ETL/ELT concepts and data pipelines.
- Strong analytical and problem-solving skills.
- Excellent attention to detail.
- Ability to learn new technologies quickly.
- Strong communication and teamwork skills.
Preferred
- Internship or project experience involving data engineering.
- Experience with AWS, Azure, or Google Cloud.
- Familiarity with Snowflake, BigQuery, Redshift, Databricks, or similar platforms.
- Exposure to Apache Airflow, dbt, Spark, Kafka, or similar technologies.
- Familiarity with Git and version-control systems.
- Basic knowledge of Docker or CI/CD.
- Experience working with APIs and JSON data.
- Familiarity with data modeling and data-warehouse concepts.
- Experience with Power BI, Tableau, or other analytics platforms.
Compensation & Benefits
The compensation for this position is $70,000–$90,000 per year, depending on technical experience, education, project work, and qualifications.
Candidates with strong SQL and Python skills, relevant internships, cloud-platform experience, or demonstrated experience building data pipelines may be considered toward the upper end of the range.
Additional benefits may include:
- Health, dental, and vision insurance
- Paid time off
- Paid holidays
- 401(k) or retirement plan
- Remote or hybrid work flexibility
- Professional development and technical training
- Company-provided equipment
- Opportunities for advancement into Data Engineer and Senior Data Engineer roles
How to Apply
Please submit your resume and, if available, a GitHub profile, portfolio, or examples of data-engineering projects.
Candidates are encouraged to highlight experience with SQL, Python, ETL/ELT pipelines, databases, cloud platforms, APIs, or data-engineering projects.
Candidates may be asked to complete a technical assessment covering SQL, Python, data transformation, and basic data-pipeline concepts.