Data Engineer

• Job Title: Data Engineer
• Location: United States (Remote)
• Work Mode: 100% Remote
• Experience: 2–7 Years
• Salary Range: $90,000 – $150,000 per year (USD)
• Employment Type: Full-Time
• Job Category: Data Engineering / IT / Software Development

Job Summary

We are seeking a skilled and motivated Data Engineer to join our growing technology team in the United States. The ideal candidate will be responsible for designing, developing, building, and maintaining scalable data pipelines, data processing systems, and data infrastructure.

The candidate should have strong programming skills in Python and SQL, experience with ETL/ELT processes, cloud platforms, data warehouses, and big data technologies.

This position offers a 100% remote work opportunity for qualified candidates across the United States.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and data architectures.
• Build and optimize ETL/ELT workflows for data extraction, transformation, and loading.
• Develop data processing solutions using Python, SQL, and other programming languages.
• Work with large structured and unstructured datasets.
• Design and maintain data warehouses, data lakes, and databases.
• Integrate data from multiple sources, APIs, and enterprise applications.
• Optimize database queries and improve data processing performance.
• Implement data validation, data quality, and monitoring processes.
• Develop and maintain cloud-based data engineering solutions.
• Collaborate with Data Scientists, Data Analysts, ML Engineers, and business teams.
• Ensure data security, reliability, and governance standards.
• Troubleshoot data pipeline issues and maintain technical documentation.

Required Skills & Qualifications

• 2–7 years of professional experience in Data Engineering or a related field.
• Strong programming knowledge of Python and SQL.
• Hands-on experience with ETL/ELT pipeline development.
• Experience with relational databases such as PostgreSQL, MySQL, or SQL Server.
• Knowledge of data warehousing and data modeling concepts.
• Experience with Apache Spark or PySpark.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with data integration and transformation tools.
• Knowledge of Apache Airflow or similar workflow orchestration tools.
• Understanding of data lakes, distributed computing, and big data technologies.
• Familiarity with Git and CI/CD practices.
• Strong analytical, debugging, and problem-solving skills.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.
• Experience with Snowflake, Databricks, Amazon Redshift, or Google BigQuery.
• Knowledge of Apache Kafka and real-time data streaming.
• Experience with Docker and Kubernetes.
• Familiarity with Terraform and infrastructure automation.
• Understanding of data governance, security, and compliance.
• Experience with dbt and modern data stack technologies.
• Knowledge of machine learning data pipelines and MLOps is an advantage.

Salary & Benefits

• Annual Salary: $90,000 – $150,000 USD.
• Competitive compensation based on experience and technical expertise.
• 100% remote work opportunity.
• Flexible working arrangements.
• Health, dental, and vision insurance.
• Paid time off and holidays.
• Retirement savings benefits, where applicable.
• Professional development and technical certification support.
• Career growth and advancement opportunities.

Work Location

United States – Fully Remote

• Candidates from eligible locations across the United States are encouraged to apply.
• Must be legally authorized to work in the United States.
• Ability to collaborate with distributed engineering teams across different US time zones.

How to Apply

Interested candidates can submit their updated resume along with contact details, relevant Data Engineering experience, technical skills, and GitHub or project portfolio links.

Equal Opportunity Employer: We welcome qualified candidates from diverse professional backgrounds and encourage applications from eligible candidates across the United States.