Junior Data Engineer (Entry-Level)

SharpAtoms; United States; On-site; USD 60,000 - 90,000; Full time

Job summary

SharpAtoms is seeking an enthusiastic Junior Data Engineer to join the Data Engineering team in the United States. This entry-level role is designed for candidates starting their careers in data engineering or related technology fields.

You will work with experienced engineers to build and optimize modern data pipelines and platforms while gaining hands-on experience with cloud data platforms such as AWS, Azure, or GCP.

Qualifications

• 0-1 year of full-time professional Data Engineering experience.
• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Software Engineering, or related field.
• Basic programming in Python and strong SQL fundamentals.

Responsibilities

• Assist in designing, developing, testing, and maintaining ETL/ELT data pipelines.
• Collect, transform, and load structured and semi-structured data from multiple sources.
• Support batch and basic real-time data processing workflows.
• Work with Python, SQL, PySpark, Spark, Databricks, Snowflake, and dbt.

Skills

SQL

Python

Analytical thinking

Communication

Education

Bachelor's or Master's degree in CS/IT/Data Science

Tools

Spark

PySpark

Databricks

Snowflake

dbt

Airflow

Kafka

Job description

SharpAtoms works with organizations undertaking data modernization, cloud, analytics, and technology transformation initiatives. We are currently evaluating early-career Data Engineering talent for upcoming project requirements and deployment opportunities.

Candidates may be considered for assignments involving data pipeline development, cloud data platforms, data warehousing, analytics engineering, and related data engineering functions. Project requirements, technology stacks, and team structures may vary by engagement.

We are looking for an enthusiastic and highly motivated Junior Data Engineer to join our Data Engineering team. This is an entry-level opportunity designed for candidates who are beginning their careers in data engineering, data analytics, or related technology fields.

You will work alongside experienced Data Engineers to build, maintain, and optimize modern data pipelines and platforms while gaining hands-on experience with real-world data engineering technologies.

Who Should Apply?

This opportunity is intended for entry-level candidates with 0-1 year of full-time professional Data Engineering experience.

• No prior full-time professional experience is required.
• Academic projects, internships, personal projects, bootcamp projects, GitHub projects, and hands-on cloud/data projects are highly valued.
• Candidates with more than 1 year of full-time professional Data Engineering experience may be better suited for experienced-level roles.

Key Responsibilities

• Assist in designing, developing, testing, and maintaining ETL/ELT data pipelines.
• Collect, transform, and load structured and semi-structured data from multiple sources.
• Support batch and basic real-time data processing workflows.
• Work with technologies such as Python, SQL, PySpark, Apache Spark, Databricks, Snowflake, and dbt.
• Gain hands-on experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Assist with cloud-based data storage, processing, and data integration solutions.

Databases & Data Warehousing

• Work with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Support modern data warehouses and lakehouse platforms such as Snowflake, Databricks, Redshift, BigQuery, or Azure Synapse.
• Assist with data modeling, schema design, and performance optimization.

Data Quality & Monitoring

• Perform data validation, cleansing, troubleshooting, and quality checks.
• Help identify and resolve data pipeline failures and data inconsistencies.
• Monitor scheduled data workflows and support reliable data delivery.
• Participate in Agile/Scrum meetings and collaborate with Data Engineers, Data Analysts, Data Scientists, and business teams.
• Use Git for version control and collaborative development.
• Maintain technical documentation for pipelines, data models, and workflows.

Required Skills & Qualifications

Education

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Software Engineering, Engineering, or a related field.
• Equivalent practical training, bootcamp, certification, or relevant project experience may also be considered.

Experience

• 0-1 year of full-time professional Data Engineering or related experience.

Technical Skills

• Strong foundational knowledge of SQL and relational database concepts.
• Basic programming knowledge in Python.
• Understanding of ETL/ELT concepts, data pipelines, data warehouses, and data modeling.
• Familiarity with one or more technologies such as Spark, PySpark, Databricks, Snowflake, dbt, Airflow, or Kafka.
• Basic knowledge of at least one cloud platform: AWS, Azure, or GCP.
• Familiarity with Git, GitHub, branching, merging, and pull requests.
• Exposure to Linux/Unix commands is a plus.

Soft Skills

• Strong analytical thinking and problem-solving abilities.
• Good communication and collaboration skills.
• Attention to detail and an interest in working with large datasets.
• Strong willingness to learn new data technologies and continuously develop technical skills.

Equal Opportunity Employer

We are an Equal Opportunity Employer. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.