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The Senior Data Engineer will design, develop, and optimize data pipelines and models, lead technical initiatives, and collaborate on data solutions across teams.
PeopleFinders.com, the premier online service for consumers to locate, contact and verify people and businesses. Over the past couple of decades the Company has quietly become one of the largest owners of public records data in the country, distributing its products over a vast network of websites.
The Senior Data Engineer is responsible for leading the design, development, and optimization of scalable, reliable data pipelines and data models that support analytics, reporting, and data-driven decision-making across the organization. This role works closely with Product, Engineering, Marketing, Finance, and Analytics teams to transform complex, multi-source data into high-quality, trusted datasets.
As a senior individual contributor, this role provides technical leadership, sets data engineering standards, and helps shape the evolution of the organization’s data platform while ensuring performance, reliability, and scalability.
- Design, build, and own scalable ETL/ELT pipelines ingesting data from third-party platforms such as HubSpot, Chargebee, Google Analytics, and other SaaS sources
- Lead data modeling and transformation efforts within Snowflake to support analytics, BI, and downstream consumers
- Architect and optimize data workflows for performance, scalability, and cost efficiency
- Integrate and manage data from operational databases including MongoDB and SQL Server
- Partner with analytics and business teams to enable high-quality dashboards and reporting in Tableau, Domo, and Power BI
- Establish and enforce best practices for data quality, validation, testing, and observability
- Monitor, troubleshoot, and resolve complex data pipeline and production issues
- Provide technical guidance and mentorship to Data Engineers and Analytics Engineers
- Collaborate with Engineering, Product, Data, and Operations teams to align data solutions with business priorities
- Contribute to data platform roadmap planning, tooling selection, and architectural decisions
- Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent practical experience
- 6+ years of experience in Data Engineering, Analytics Engineering, or related roles
- Advanced SQL skills and extensive experience working with large datasets in cloud data warehouses
- Deep hands-on experience with Snowflake, MongoDB, SQL Server and other database technologies
- Proven experience designing, building, and maintaining complex ETL/ELT pipelines
- Experience supporting BI and analytics platforms such as Tableau, Domo, and Power BI
- Strong understanding of data modeling, dimensional modeling, and analytics engineering best practices
- Ability to lead technical initiatives and communicate complex concepts to technical and non-technical stakeholders
- Experience with modern data stack tools such as dbt, Airflow, Fivetran, or Stitch
- Experience designing semantic models or enterprise datasets optimized for Power BI
- Experience supporting marketing, subscription, revenue, or product analytics use cases
- Familiarity with APIs, event-driven data, and semi-structured data formats
- Experience optimizing cloud data warehouse performance and cost at scale
- Exposure to data governance, security, privacy, or compliance-aware environments
- Experience acting as a technical lead or senior individual contributor within a data team
Benefits
- Flexible PTO
- 6% 401K match
- 100% of the cost paid for the employee for medical, dental and vision
- 60% of the cost paid for dependents for medical, dental and vision
Top Skills
Airflow
Chargebee
Dbt
Domo
Fivetran
Google Analytics
Hubspot
MongoDB
Power BI
Snowflake
SQL
SQL Server
Stitch
Tableau
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