Data Engineer

Evlo AI; Los Angeles (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

Evlo AI seeks a data engineer to own the design, implementation, and scaling of core data infrastructure. You will build reliable pipelines for high-throughput event data and batch analytics, enabling seamless access and high data quality across the tech stack.

You will work with analytics engineers and data scientists to model data for BI tools and ML applications, and contribute to data observability, testing, and best practices across code reviews and version control.

Qualifications

• 3–6 years of experience building production data pipelines and data warehouses.
• Advanced SQL and Python programming skills.
• Experience with orchestration tools (Airflow, Prefect, or Dagster).

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL processes.
• Manage cloud data warehousing infrastructure (Snowflake, BigQuery, or Redshift).
• Implement data quality checks and monitoring for observability.
• Collaborate with analysts and data scientists to model data for BI and ML.
• Write clean, version-controlled code and participate in code reviews.

Skills

SQL

Python

Airflow

Data Modeling

Tools

Snowflake

BigQuery

Redshift

dbt

Apache Airflow

Prefect

Dagster

Terraform

Kafka

Spark

Job description

About The Role

The role owns the design, implementation, and scaling of the core data infrastructure, building reliable pipelines that process high-throughput event data and batch analytics.

The data team works closely with analytics engineering and business stakeholders to ensure high data quality, seamless access, and performant data models across the entire tech stack.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL processes using Python, SQL, and Apache Airflow
• Manage cloud data warehousing infrastructure (Snowflake, BigQuery, or Redshift), optimizing query performance and managing compute costs
• Implement data quality checks, automated monitoring, and data observability frameworks to catch pipeline failures early
• Collaborate with analytics engineers and data scientists to model data for consumption in BI tools and machine learning applications
• Write clean, version-controlled code using Git, participating in code reviews and establishing data engineering best practices

What We Are Looking For

• 3–6 years of experience in data engineering, building production‑grade data pipelines and data warehouses
• Advanced SQL and Python programming skills, with strong proficiency in orchestration tools like Apache Airflow, Prefect, or Dagster
• Deep experience with cloud data warehouses (Snowflake, BigQuery) and modern data stack tools (dbt)
• Familiarity with distributed data processing frameworks such as Apache Spark, Kafka, or Flink
• Bonus: Experience with infrastructure-as-code (Terraform) and stream processing architectures