Data & Analytics Engineer — Remote

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

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.