Assistant Manager

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. 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.
This is an excellent opportunity for candidates looking to build a career in data engineering and gain hands-on experience with modern data technologies, cloud platforms, and big data solutions.

Success Metrics

Delivery of reliable and scalable data pipelines.
High data quality and accuracy standards.
Timely resolution of data issues.
Effective collaboration with cross-functional teams.
Continuous learning and adoption of best practices.

Key Responsibilities

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 requirements.
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 Qualifications

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 tools such as Git.
Strong analytical and problem-solving skills.
Excellent communication and teamwork abilities.

Preferred Qualifications

Experience with cloud platforms such as AWS, Azure, or GCP.
Familiarity with data engineering tools such as Apache Spark, Airflow, Databricks, or Kafka.
Exposure to Snowflake, Redshift, BigQuery, or Synapse.
Understanding of REST APIs and data ingestion techniques.
Knowledge of CI/CD practices and DevOps fundamentals.
Relevant certifications in cloud or data technologies.

Technical Skills
Required

SQL
Python
Data Modeling Fundamentals
ETL/ELT Concepts
Relational Databases (SQL Server, PostgreSQL, MySQL)
Git

Preferred

Apache Spark
Airflow
Databricks
Snowflake
Azure Data Factory / AWS Glue
Kafka
Power BI or Tableau