Junior Data Engineer

TJHelpers is committed to developing strong engineering teams through mentorship, real project experience, and our “Helpers as a Service” model. We provide structured growth, hands-on practice, and a supportive environment where engineers can evolve quickly and meaningfully.

We are looking for a Junior Data Engineer to join our team and help build and maintain reliable data pipelines, transformations, and datasets for modern products in fintech, AI, telecommunications, healthcare, and other data-driven domains.

This is a great opportunity to work with real-world data, grow in data engineering, and gain hands-on experience with SQL, Python, ETL/ELT processes, and modern data platforms.

Responsibilities

• Support the development and maintenance of data pipelines and ETL/ELT processes 
• Collect, clean, transform, and load data from databases, APIs, files, and external systems 
• Write and optimize SQL queries for data preparation and transformation 
• Assist in building datasets for analytics, reporting, and internal products 
• Support data quality, consistency, and reliability across pipelines and datasets 
• Work with structured and semi-structured data 
• Participate in troubleshooting and improving data processes 
• Assist in monitoring and improving data pipeline reliability and performance 
• Collaborate with engineers, analysts, and product teams 

Requirements

• Basic understanding of data engineering concepts and data pipeline architecture 
• Hands-on experience writing SQL queries and working with Python 
• Understanding of relational databases such as PostgreSQL or MySQL 
• Ability to write SQL queries using joins, filtering, aggregations, and transformations 
• Basic understanding of ETL/ELT processes 
• Understanding of data modeling and data transformation principles 
• Familiarity with data formats such as CSV and JSON and working with APIs 
• Basic understanding of structured and semi-structured data 
• Analytical thinking and attention to detail 

• Motivation to learn and grow in a technical environment 

   

Nice to Have

• Basic experience with Pandas 
• Basic familiarity with Spark or PySpark 
• Familiarity with Airflow, dbt, or similar tools 
• Understanding of data warehouses such as BigQuery, Snowflake, or Redshift 
• Familiarity with cloud platforms such as AWS, GCP, or Azure 
• Familiarity with Git 
• Experience with BI or analytics tools 

• Interest in data platforms, analytics engineering, or ML/AI workflows 

   

What We Offer

• Work with real production data systems and modern technologies 
• Mentorship from experienced engineers and tech leads 
• Clear growth path to Middle Data Engineer level 
• Supportive engineering culture focused on learning and practical development 
• Flexible schedule and fully remote work opportunities