Data Engineer - 17585

Role: Data Engineer
Priority Location: Global
Working Hours: 40hrs/week, flexible hours with the ability to overlap between 1:00 PM – 3:00 PM ET
Type of contract: Full-Time
Type of job: Remote
Salary Range: $4,000 to $5,500 per month
The final offer is at the client’s discretion and will depend on the candidate’s interview result, skills, and experience.

About the Role: We're looking for a Data Engineer with solid SQL expertise and a genuine interest in data modeling. You'll work with ClickHouse (or ramp up quickly if you're coming from another OLAP system) to build and maintain our analytical data infrastructure. This is a hands-on role focused on data modeling, building reliable pipelines, and delivering clean, reliable data to the rest of the team. You will work on projects that require sophisticated data grouping and analytical techniques—delivering structured outputs to support strategic decision making.

Key Responsibilities
Data Modeling & SQL:

• Design and maintain robust data models optimized for analytical workloads.
• Write clear, well-structured SQL queries and transformations for data extraction and integration.

Data Pipeline & Platform Management:

• Build, manage, and optimize data pipelines that feed our analytics systems.
• Work with ClickHouse table engines, partitioning strategies, and materialized views to ensure performance and scalability.

Collaboration & Quality:

• Collaborate effectively with analysts and product teams to understand data needs and deliver tailored data solutions.
• Document data models, pipeline architecture, and maintain high standards for data quality and integrity.

Qualifications & Skills:

• Experience: 
  • Minimum 5+ years of professional experience in software or data engineering with focus on Data Analysis, Transformation, and ETL (Extract, Transform, Load) pipelines.
  • Proven ability to structure complex datasets and articulate design and implementation choices clearly. NLP/LLM skills are not required for this role.
• Primary Skills: Expert-level proficiency in Python and SQL, with a strong focus on writing clean, maintainable code for data processing.
• Key Platforms (Must have at least one):
  • ClickHouse (Ideal)
  • Snowflake
  • Databricks
• Nice-to-Have:
  • Experience with MongoDB / NoSQL databases
  • Knowledge of Node.js 
• Portfolio is required for evaluation (e.g., GitHub repository, live project examples)