Data Engineer

Evlo AI; Miami (FL); On-site; USD 110,000 - 150,000; Full time

Job summary

Evlo AI is seeking a data engineer to own the design, implementation, and scaling of core data infrastructure and high-throughput pipelines powering analytical workloads across the business.

You will collaborate with data analysts, backend engineers, and product stakeholders to ensure reliable data ingestion, transformation, and accessibility, while driving performance and cost optimization.

Qualifications

• 3-6 years of data engineering, backend development, or analytics engineering with a focus on pipeline orchestration
• Advanced SQL and Python proficiency; hands-on experience with workflow orchestrators like Apache Airflow or Prefect
• Proven experience building and maintaining data warehouses in cloud environments such as AWS, GCP, or Azure
• Solid understanding of distributed computing concepts, data modeling (Kimball methodology), and performance tuning
• Bonus: Experience with real-time streaming tools (Kafka, Flink) and Infrastructure-as-Code (Terraform)

Responsibilities

• Design, build, and optimize scalable ETL and ELT data pipelines using Python, SQL, and Apache Spark
• Manage cloud data warehousing infrastructure (Snowflake, BigQuery, or Redshift) and enforce dimensional modeling best practices
• Implement automated data quality monitoring, anomaly detection, and schema migration frameworks
• Collaborate with analytics and engineering teams to define data contracts, optimize query performance, and reduce cloud compute costs
• Write clean, version-controlled code using Git, and participate in code reviews and infrastructure design discussions

Skills

Advanced SQL

Python

Apache Airflow

Prefect

Cloud data warehousing (AWS/GCP/Azure)

Data modeling (Kimball)

Distributed computing concepts

Terraform / IaC

Real-time streaming (Kafka/Flink)

Tools

Snowflake

BigQuery

Redshift

Apache Spark

Git

Terraform

Job description

About The Role

The role owns the design, implementation, and scaling of core data infrastructure and high-throughput pipelines that power analytical workloads across the business. The team works closely with data analysts, backend engineers, and product stakeholders to ensure reliable data ingestion, transformation, and accessibility.

Key Responsibilities

• Design, build, and optimize scalable ETL and ELT data pipelines using Python, SQL, and Apache Spark
• Manage cloud data warehousing infrastructure (Snowflake, BigQuery, or Redshift) and enforce dimensional modeling best practices
• Implement automated data quality monitoring, anomaly detection, and schema migration frameworks
• Collaborate with analytics and engineering teams to define data contracts, optimize query performance, and reduce cloud compute costs
• Write clean, version-controlled code using Git, and participate in code reviews and infrastructure design discussions

What We Are Looking For

• 3-6 years of experience in data engineering, backend development, or analytics engineering with a focus on pipeline orchestration
• Advanced SQL and Python proficiency; hands-on experience with workflow orchestrators like Apache Airflow or Prefect
• Proven experience building and maintaining data warehouses in cloud environments such as AWS, GCP, or Azure
• Solid understanding of distributed computing concepts, data modeling (Kimball methodology), and performance tuning
• Bonus: Experience with real-time streaming tools (Kafka, Flink) and Infrastructure-as-Code (Terraform)