Data Engineer

Harrison Clarke; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

Harrison Clarke is seeking a Data Engineer / Analytics Engineer to build the data foundation behind a rapidly scaling business. This hands-on role sits at the intersection of data engineering, analytics, and business intelligence, bringing structure to fragmented data and standardizing KPIs.

You will develop scalable data models, ETL/ELT pipelines, and reporting infrastructure, with opportunities to expand into advanced data science as the function grows.

Qualifications

• 3+ years of experience in Data Engineering or Analytics Engineering.
• Strong SQL skills with production data experience.
• Experience designing data models for reporting and analytics.

Responsibilities

• Design and build scalable analytical data models that support reporting and analytics.
• Develop and maintain ETL/ELT pipelines and transformation workflows across multiple data sources.
• Establish consistent definitions for core business KPIs and metrics.
• Build and organize dashboards and reporting used by business and product teams.
• Work closely with stakeholders to translate business questions into data solutions.
• Investigate data quality issues and improve reliability of underlying data.
• Develop aggregation tables and optimized datasets for analytics and application use cases.
• Perform deeper analysis to identify trends, opportunities, and problems.
• Partner with Engineering, Product, and business leaders to improve data infrastructure.
• Help establish foundations for future initiatives around entity resolution and identity matching.

Skills

SQL

Data modeling

ETL/ELT

BI dashboards

Data quality

Stakeholder communication

Python

Statistical analysis

Tools

dbt

ClickHouse

Job description

Remote | US

We're working with a fast-growing technology company looking for a Data Engineer / Analytics Engineer to build the data foundation behind a rapidly scaling business.

This is a highly hands-on role sitting at the intersection of data engineering, analytics, and business intelligence. You'll be responsible for bringing structure to fragmented data, building reliable analytical models, standardizing KPIs, and creating the reporting infrastructure that enables teams to make better decisions.

Over time, the role will expand into more sophisticated data science initiatives, including entity resolution and identity matching.

What you'll do

• Design and build scalable analytical data models that support reporting, analytics, and downstream applications
• Develop and maintain ETL/ELT pipelines and transformation workflows across multiple data sources
• Establish consistent definitions for core business KPIs and metrics
• Build and organize dashboards and reporting used by business and product teams
• Work closely with stakeholders to understand business questions and translate them into robust data solutions
• Investigate data quality issues, anomalies, and inconsistencies and improve the reliability of the underlying data
• Develop aggregation tables and optimized datasets for analytics and application use cases
• Perform deeper analysis when needed to identify trends, opportunities, and problems
• Partner closely with Engineering, Product, and business leaders to improve the company's overall data infrastructure
• Help establish the foundations for future initiatives around entity resolution, identity matching, and more advanced data science

What we're looking for

• 3+ years of experience in Data Engineering, Analytics Engineering, Data Analytics, or a closely related role
• Strong SQL skills and experience working directly with production data
• Experience designing data models for reporting and analytics
• Hands-on experience building ETL/ELT pipelines and transformation workflows
• Experience working with BI/reporting tools and building reliable dashboards
• Strong understanding of data quality, metric definitions, and analytical best practices
• Ability to work closely with non-technical stakeholders and translate ambiguous business questions into practical data solutions
• Comfortable operating in a fast-moving environment where you'll have significant ownership
• Some experience with Python and/or statistical analysis is a plus

Nice to have

• Experience with dbt, ClickHouse, or other analytical/OLAP technologies
• Experience working with high-volume event, transactional, or behavioral data
• Experience with attribution, marketing/ad-tech, marketplaces, or other complex data environments
• Exposure to entity resolution, record linkage, identity graphs, or graph databases
• Experience partnering with Data Science or ML teams

Why this role?

This is an opportunity to become a foundational member of the data function and have a meaningful impact on how the company understands and uses its data.

You'll have significant ownership over the data models, metrics, pipelines, and analytical infrastructure that the wider organization relies on, while also having the opportunity to grow into more advanced data science and entity-resolution work as the function develops.