Lead Data Engineer

**Please note that we are not accepting candidate submissions from third-party recruiting agencies, staffing firms, or search firms for this opportunity. All candidates must apply directly.
Location: Remote (USA)
Term: 3 Months, extendable
Type: Contract
Hourly Rate: $70-$80/hr (Dependent on Experience)
This is an opportunity to join a growing data and analytics team on a contract assignment focused on building and scaling a modern cloud-based data platform. You will have the chance to shape data architecture, improve platform reliability, and deliver solutions that support analytics and business decision-making across the organization.
The Company
They are an organization investing in the continued growth of their data and analytic capabilities. Their focus is on creating scalable, cloud-native data solutions that improve access to high-quality data and support business performance. You will work within a collaborative environment that values automation, engineering best practices, and continuous improvement. This project offers the opportunity to contribute to a strategically important data platform initiative.
The Role and Deliverables
Design and develop scalable data pipelines and workflows within a cloud-native environment.
Build and maintain ingestion frameworks for structured and unstructured data sources.
Develop data models and datasets to support analytics and reporting requirements.
Create, optimize, and support ELT/ETL processes using modern data engineering practices.
Automate orchestration, monitoring, and operational processes to improve platform reliability and efficiency.
Collaborate with technical and business stakeholders to deliver scalable, high-quality data solutions.
Your Skills & Experience
Strong experience with Google Cloud Platform, including BigQuery, Cloud Storage, Dataflow, and Cloud Composer or comparable orchestration tools.
Proven capability building scalable data pipelines and data ingestion frameworks.
Advanced SQL and Python development skills.
Strong understanding of data modeling, data warehousing, and analytics concepts.
Experience designing, implementing, and optimizing ELT/ETL workflows.
Familiarity with CI/CD practices, infrastructure automation, and software engineering best practices.
Experience implementing data quality, monitoring, observability, and platform reliability processes.
Ability to work effectively with both technical and non-technical stakeholders.
Experience with dbt, Looker, or similar modern data tooling is beneficial.
Strong problem-solving skills with a focus on ownership, collaboration, and continuous improvement.

Work arrangement
Yes