Data Engineer | Remote

Crossing Hurdles; United States; Remote; USD 280,000 - 450,000; Full time

Job summary

Crossing Hurdles is seeking a Member of Technical Staff in Data Engineering to architect and deploy a zero-to-one data platform remotely. You will build the data warehouse, ingestion and ETL/ELT pipelines, and robust data models to support AI-driven analytics across engineering, product, and business domains.

You will own instrumentation, data quality, observability, and self-service analytics, while leveraging modern tools like Snowflake, BigQuery, Databricks, and Airflow.

Qualifications

• Staff-level engineering expertise with hands-on experience building production data platforms.
• Led greenfield data platform design and implementation from scratch.
• Deep understanding of data warehouses, ETL/ELT architectures, data modeling, orchestration, and distributed processing.
• Strong proficiency in SQL and Python with software engineering fundamentals for reliable data infra.
• Experience with modern data tech such as Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Dagster.
• Focus on data quality, lineage, observability, access controls and production data reliability.

Responsibilities

• Build our data platform from zero: architect and implement internal data warehouse, ingestion infra, ETL/ELT pipelines, core models.
• Create agent-ready data foundations: design datasets and interfaces for AI agents to safely discover, query, and use.
• Turn messy data into trusted sources of truth and high-quality outputs.
• Enable self-service analytics for engineering, product, and business teams without manual requests.
• Own analytics infrastructure: establish event tracking, data models, and reporting foundations for product usage.
• Automate data operations using AI coding agents to accelerate pipelines, validation, documentation, monitoring, and troubleshooting.

Skills

SQL

Python

Data engineering

ETL/ELT

Data warehousing

Data quality

Observability

Tools

Snowflake

BigQuery

Redshift

Databricks

dbt

Airflow

Dagster

Job description

Position: Member of Technical Staff, Data Engineering

Type: Full-time

Compensation: $280K - $450K/yr

Location: Remote

Commitment: 10-40 hrs/week

Role Responsibilities

• Build our data platform from zero: Architect and implement our internal data warehouse, ingestion infrastructure, ETL/ELT pipelines, and core data models.
• Create agent-ready data foundations: Design reliable, well-documented datasets and interfaces that AI agents can safely discover, query, and use.
• Turn messy data into trusted systems: Transform fragmented operational and product data into consistent, high-quality sources of truth.
• Enable self-service analytics: Build the infrastructure that allows engineering, product, and business teams to answer questions independently without relying on manual data requests.
• Own product analytics infrastructure: Establish the event tracking, instrumentation, data models, and reporting foundations needed to understand product usage and performance.
• Automate data operations: Leverage AI coding agents and intelligent automation to accelerate pipeline development, data validation, documentation, monitoring, and troubleshooting.

Requirements

• Staff-level engineering expertise with extensive hands-on experience building and operating production data platforms.
• Proven greenfield experience: You've personally led the design and implementation of a data platform from scratch.
• Deep understanding of data warehouses, ETL/ELT architectures, data modeling, orchestration, and distributed data processing.
• Strong proficiency in SQL and Python, with the software engineering fundamentals needed to build reliable data infrastructure.
• Experience with modern data technologies such as Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Dagster, or equivalent tools.
• Strong understanding of data quality, lineage, observability, access controls, and production data reliability.