Remote ETL Data Engineer - Flexible, High-Impact Pipelines

INDI Staffing Services; United States; Hybrid; USD 110,000 - 160,000; Full time

Benefits offered by this job

Diversity & inclusion

Tailored compensation

Tech-driven tools

Autonomous workflow

Generous leave policies

Mentorship & growth

Job summary

INDI Staffing Services seeks an ETL/Data Engineer to design and implement scalable data pipelines and processing systems. You will transform raw data into actionable insights and shape strategic data architecture.

Responsibilities include building ETL workloads, optimizing architectures, ensuring data quality, and collaborating with analysts and business teams to deliver robust, cost-efficient solutions.

Qualifications

• 3+ years in ETL development, data engineering, or related fields.
• Strong knowledge of SQL, Python, and data processing frameworks.
• Experience with data warehousing concepts and cloud-based data platforms.
• Understanding of data modeling and performance optimization.
• Familiarity with version control systems and data pipeline orchestration tools.
• Knowledge of data quality assurance and monitoring best practices.
• Advanced level of English.

Responsibilities

• Design, develop, and maintain scalable ETL pipelines and data processing systems.
• Build and optimize data architectures to support efficient ETL processes.
• Implement data quality checks and monitoring for reliability.
• Collaborate with data analysts and business teams to gather requirements.
• Optimize data storage and retrieval for performance and cost-efficiency.
• Troubleshoot and resolve complex data pipeline issues while maintaining stability.

Skills

ETL development

SQL

Python

Data processing frameworks

Cloud data warehousing

Data modeling

Version control

Data quality

English (advanced)

Automation

Tools

Data tooling

Job description

INDI Staffing Services seeks an ETL/Data Engineer to design and implement scalable data pipelines and processing systems. You will transform raw data into actionable insights and shape strategic data architecture.

Responsibilities include building ETL workloads, optimizing architectures, ensuring data quality, and collaborating with analysts and business teams to deliver robust, cost-efficient solutions.