Location: Remote (U.S.)
Duration: 11 Months (Contract)t
We are seeking a highly skilled Senior Data Engineer (Data Modeler) to design and implement large-scale data models and infrastructure for advanced analytics and business intelligence solutions. The ideal candidate will have a strong background in data modeling, database design, and data pipeline optimization, with a passion for delivering high-quality, reliable, and scalable data solutions in a collaborative environment.
Design and implement data models supporting both operational and analytical data processing systems.
Ensure seamless integration of data from diverse sources such as databases, APIs, and streaming platforms.
Optimize data processing performance through effective partitioning, indexing, and query tuning strategies.
Establish and maintain data quality checks and validation mechanisms to ensure high-quality, consistent data.
Implement data security measures in collaboration with information security teams — including encryption, access controls, and compliance with data protection regulations.
Collaborate closely with data scientists, analysts, software engineers, and business stakeholders to deliver effective data solutions.
Develop and maintain data infrastructure components, including data warehouses, data lakes, and ETL/ELT pipelines.
Set up auditing, monitoring, and alerting systems to ensure data governance and operational excellence.
Troubleshoot data-related issues, identify root causes, and implement remediation strategies.
Continuously evaluate emerging technologies and frameworks to enhance data engineering capabilities and performance.
5–7 years of professional experience in data modeling, including both 3NF (Third Normal Form) and dimensional modeling.
Proficiency in SQL for advanced data analysis and query optimization.
Strong problem-solving, analytical thinking, and decision-making skills.
Proven ability to collaborate across cross-functional teams and contribute to shared goals.
Strong communication and documentation skills.
Experience ensuring data quality, reliability, and governance within enterprise systems.
Expertise in data warehousing and data lake architectures.
Familiarity with cloud-based data platforms (e.g., AWS, Azure, GCP).
Experience with ETL/ELT tools, data orchestration frameworks, and data version control.
Understanding of data lifecycle management, metadata management, and data cataloging.
Background in business intelligence and analytics environments.
Bachelor’s degree in Computer Science, Information Systems, or a related technical discipline.
Equivalent professional training or experience will be considered in place of formal education.