Assistant Manager

Job summary

Job Description: Junior Data Engineer (Hybrid, Woonsocket, RI) Job Summary We are seeking a motivated and detail-oriented Junior Data Engineer to join our growing data team. In this role, you will support the design, development, and maintenance of data pipelines, data integration processes, and analytical data platforms.

Qualifications

• This is an excellent opportunity for candidates looking to build a career in data engineering and gain hands-on experience with modern data
• Document data flows, technical processes, and data lineage.
• Follow data governance, security, and compliance standards.
• Participate in code reviews and contribute to continuous improvement initiatives.
• Required
• Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
• 1–2 years of experience in data engineering, software engineering, or data-related roles.
• Strong understanding of SQL and relational databases.
• Basic programming knowledge in Python, Java, or Scala.
• Understanding of ETL concepts and data integration processes.
• Familiarity with data warehousing concepts and dimensional modeling.
• Knowledge of version control

Responsibilities

• In this role, you will support the design, development, and maintenance of data pipelines, data integration processes, and analytical data platforms.
• You will work closely with senior data engineers, data analysts, data scientists, and business stakeholders to ensure reliable, high-quality data is available for reporting, analytics, and business decision-making.
• Develop, maintain, and monitor ETL/ELT data pipelines.
• Extract, transform, and load data from various source systems into data warehouses and data lakes.
• Assist in building and optimizing data models for analytics and reporting.
• Perform data validation, cleansing, and quality checks to ensure data accuracy.
• Support data integration efforts across multiple systems and platforms.
• Write and optimize SQL queries for data extraction and analysis.
• Troubleshoot data pipeline issues and implement fixes under guidance.
• Collaborate with data analysts, data scientists, and business teams to understand data

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