Data Engineer

Senior Data Engineer

Location: Remote (Travel up to 10 - 20%)

Contract

Job Summary

We are seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data solutions that support business intelligence, analytics, and data-driven decision-making. The ideal candidate will have strong expertise in Python, SQL, and ETL development, along with experience building robust data pipelines and working with modern cloud-based data platforms.

This role is fully remote, with 10%- 20% travel for client meetings, project workshops, and team collaboration.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
• Build and optimize complex SQL queries, stored procedures, and database solutions.
• Develop data integration solutions using Python and industry-standard ETL tools.
• Design and implement data models to support reporting, analytics, and business requirements.
• Ensure data quality, integrity, security, and governance across data platforms.
• Monitor, troubleshoot, and optimize data workflows and pipeline performance.
• Collaborate with data architects, analysts, business stakeholders, and engineering teams.
• Support cloud-based data warehousing and data lake initiatives.
• Participate in code reviews and promote engineering best practices.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 7+ years of experience in Data Engineering or related roles.
• Strong hands-on experience with Python for data processing and automation.
• Advanced proficiency in SQL and relational database systems.
• Extensive experience designing and supporting ETL/ELT processes.
• Experience with data warehousing concepts and dimensional modeling.
• Strong understanding of data quality, performance tuning, and optimization.
• Experience with source control systems such as Git.

Preferred Qualifications

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with modern data tools such as Airflow, dbt, Spark, Databricks, or Kafka.
• Knowledge of CI/CD pipelines and DevOps practices.
• Experience supporting large-scale enterprise data environments.

Travel Requirement

• Ability to travel up to 25% for client engagements, workshops, and team meetings.