Analytics Engineer

LandEarly; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

LandEarly is seeking an Analytics Engineer to turn product and application data into trusted, well-modeled datasets. You will design data models and pipelines, partner with product and engineering to define metrics, and own the transformation layer with testing and documentation.

You will build dashboards and self-serve tools, monitor data quality and pipeline health, and collaborate to improve data warehouse reliability and scalability in a fast-moving environment.

Qualifications

• Strong SQL background and data modeling concepts.
• Experience with a modern data transformation framework such as dbt.
• Familiarity with Snowflake, BigQuery, or Redshift.
• Ability to communicate clearly with technical and non‑technical stakeholders.
• Comfort working in a fast‑moving environment with evolving priorities.

Responsibilities

• Design, build, and maintain data models and transformation pipelines to produce analysis-ready datasets.
• Collaborate with product, engineering, and operations to define key metrics and ensure consistent definitions.
• Own the data transformation layer (e.g., dbt), including testing and documentation.
• Build dashboards and self-serve reporting tools for stakeholders to answer questions.
• Monitor data quality and pipeline health and troubleshoot issues.
• Collaborate to improve data warehouse reliability and scalability.

Skills

SQL

Data modeling

dbt

Cloud data warehouses

Communication

Tools

dbt

Airflow

Looker

Mode

Metabase

Python

Job description

LandEarly is looking for an Analytics Engineer to help turn our product and application data into reliable, well‑modeled datasets that the whole company can trust. LandEarly is an auto‑apply platform that helps job seekers find fresh postings, tailor their materials, and submit applications quickly, and this role will be central to understanding how people use the product and where it can improve.

What you'll do

• Design, build, and maintain data models and transformation pipelines that turn raw application and product data into clean, analysis‑ready tables
• Partner with product, engineering, and operations teams to define key metrics (such as application volume, match quality, and conversion rates) and ensure consistent definitions across the company
• Own the data transformation layer (e.g., dbt or similar), including testing, documentation, and version control
• Build and maintain dashboards and self‑serve reporting tools so stakeholders can answer their own questions
• Monitor data quality and pipeline health, and troubleshoot issues before they affect downstream reporting
• Collaborate with data engineers and analysts to improve the reliability and scalability of the data warehouse

What we’re looking for

• Experience as an analytics engineer, data engineer, or data analyst with a strong SQL background
• Hands‑on experience with a modern data transformation framework such as dbt
• Familiarity with cloud data warehouses (e.g., Snowflake, BigQuery, or Redshift)
• Strong understanding of data modeling concepts (dimensional modeling, star schemas, etc.)
• Ability to communicate clearly with both technical and non‑technical stakeholders
• Comfort working in a fast‑moving environment with evolving priorities

Nice to have

• Experience with workflow orchestration tools (e.g., Airflow, Dagster)
• Familiarity with BI tools such as Looker, Mode, or Metabase
• Python or scripting experience for data pipeline automation