Data Engineer

Evlo AI; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Evlo AI is seeking a data engineer to own the design, implementation, and scaling of core data infrastructure and ETL pipelines powering analytics, ML, and business operations. You will collaborate with data scientists, product managers, and software engineers to ensure high-throughput data processing and optimal data modeling in cloud data warehouses.

The role emphasizes building scalable pipelines, data quality, and governance with modern tools such as Airflow, dbt, and Terraform, while

Qualifications

• 3–6 years of experience in data engineering, backend development, or analytics engineering focusing on data pipelines.
• Advanced SQL and Python programming skills with hands-on data modeling (dimensional modeling, star schema).
• Production experience with cloud data warehouses (Snowflake, BigQuery, or Redshift) and workflow orchestrators (Airflow, Dagster).
• Familiarity with data governance, security best practices, and CI/CD pipelines for data engineering.
• Bonus: experience with streaming data technologies like Kafka or Flink, and infrastructure-as-code tools such as Terraform.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL workflows using Python, SQL, and orchestration tools.
• Architect and optimize cloud data warehouse schemas, tables, and views for performant analytics.
• Implement data quality checks, monitoring, and data lineage to ensure data integrity.
• Collaborate with backend engineers to ingest event data from microservices and external APIs.
• Write modular, tested infrastructure-as-code and data transformation logic using dbt and Git.

Skills

SQL

Python

Data modeling

ETL pipelines

Tools

Snowflake

BigQuery

Redshift

Airflow

Dagster

dbt

Terraform

Job description

About The Role

The role owns the design, implementation, and scaling of core data infrastructure and reliable ETL pipelines that power analytics, machine learning, and business operations across the organization.

About The Role

The role owns the design, implementation, and scaling of core data infrastructure and reliable ETL pipelines that power analytics, machine learning, and business operations across the organization.

The team works closely with data scientists, product managers, and software engineers to ensure high-throughput data processing and optimal data modeling in cloud data warehouses.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL workflows using Python, SQL, and modern orchestration tools like Airflow or Prefect
• Architect and optimize cloud data warehouse schemas, tables, and views in Snowflake or BigQuery to ensure performant analytical queries
• Implement robust data quality checks, automated monitoring, and data lineage tracking to maintain high standards of data integrity
• Collaborate with backend engineers to ingest event data from microservices and external APIs into central storage layers
• Write clean, modular, well-tested infrastructure-as-code and data transformation logic using dbt and Git workflows

What We Are Looking For

• 3–6 years of experience in data engineering, backend development, or analytics engineering with a focus on data pipelines
• Advanced SQL and Python programming skills, with hands‑on expertise in data modeling concepts (dimensional modeling, star schema)
• Production experience with cloud data warehouses (Snowflake, BigQuery, or Redshift) and workflow orchestrators (Apache Airflow, Dagster)
• Familiarity with data governance, security best practices, and CI/CD pipelines for data engineering
• Bonus: Experience with streaming data technologies like Kafka or Flink, and infrastructure-as-code tools such as Terraform