Data Engineer - Build Scalable Pipelines & Data Warehouses

Evlo AI; Dallas (TX); On-site; USD 110,000 - 170,000; Full time

Job summary

Evlo AI is seeking a data engineer to own the data infrastructure powering analytics and product decisions. You will design batch and streaming pipelines, model data warehouses, and maintain trustworthy data at scale.

Collaborate with analytics engineers, data scientists, and backend teams to convert raw streams and operational data into clean datasets. You will build scalable ETL/ELT pipelines, optimize Snowflake/BigQuery/Redshift layers, and implement data quality checks.

Qualifications

• Must have 3–6 years of data/analytics/backend engineering with heavy data focus.
• Proficient in production-grade, tested pipeline code using SQL and Python.
• Hands-on experience with a modern data warehouse and an orchestrator.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines using Python, SQL, and Airflow/Dagster.
• Model and optimize data warehouse layers (Snowflake/BigQuery/Redshift).
• Build and operate streaming pipelines with Kafka/Kinesis.
• Define semantic layers, dbt models, and data contracts across teams.
• Implement data quality and observability checks with Great Expectations or dbt tests.
• Own IaC for data tooling (Terraform, CI/CD) across cloud environments.
• Document pipelines, runbooks, and data lineage; participate in on-call rotation.

Skills

Advanced SQL

Python

Data engineering

Collaboration

Education

Bachelor's degree in CS/Engineering

Tools

Airflow

Dagster

Prefect

dbt

Snowflake

BigQuery

Redshift

Kafka

Kinesis

Terraform

Job description

Evlo AI is seeking a data engineer to own the data infrastructure powering analytics and product decisions. You will design batch and streaming pipelines, model data warehouses, and maintain trustworthy data at scale.

Collaborate with analytics engineers, data scientists, and backend teams to convert raw streams and operational data into clean datasets. You will build scalable ETL/ELT pipelines, optimize Snowflake/BigQuery/Redshift layers, and implement data quality checks.