Lead Data Engineer

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New York / $70 - $80 hour

INFO

Salary

RATE:

$70 - $80

Location

LOCATION

New York

Job Type
JOB TYPE

Contract

**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.


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