Data Engineer

Evlo AI; San Francisco (CA); On-site; USD 120,000 - 190,000; Full time

Job summary

Evlo AI is seeking a Data Engineer to design and operate data infrastructure powering product analytics, reporting, and operational decisions. You will own batch and streaming pipelines across multiple data sources and collaborate with analytics engineers, data analysts, and product teams.

Responsibilities include building scalable ELT workflows, modeling datasets with dbt, and implementing data quality, lineage, and monitoring to ensure trustworthy data for dashboards and decisions.

Qualifications

• 3–8 years of experience in data engineering, analytics engineering, or closely related software role.
• Strong SQL and Python skills with maintainable transformations, tests and production automation.
• Hands-on experience building and operating data pipelines with Airflow, Dagster, Kafka, Spark or equivalent.
• Proficiency with cloud data warehouses such as Snowflake, BigQuery, Redshift, or Databricks.
• Experience with dbt or comparable transformation and data modeling frameworks.
• Bachelor's degree or equivalent practical experience in a technical field.
• Bonus: experience with Terraform, Kubernetes, streaming architectures, observability tools and cloud platforms (AWS, GCP, Azure)

Responsibilities

• Design, build, and maintain batch and streaming data pipelines using Python, SQL, Airflow, and cloud services.
• Develop scalable ELT workflows ingesting data from apps, APIs, event streams, and SaaS platforms into Snowflake, BigQuery, or equivalents.
• Model datasets using dimensional modeling and dbt with ownership, documentation, and reuse in mind.
• Implement data quality checks, lineage, and monitoring to ensure freshness and accuracy for reporting.
• Optimize warehouse queries and pipelines to improve reliability and control costs.
• Partner with analysts to define metrics, contracts, and source-of-truth tables for reporting.
• Review code, improve tests and deployment workflows, and contribute to engineering standards.

Skills

SQL

Python

Data pipelines

Education

Bachelor's degree in CS/Engineering/Math/Stats

Tools

Airflow

Dagster

Kafka

Spark

Snowflake

BigQuery

Redshift

Databricks

Terraform

Kubernetes

Job description

About The Role

The Data Engineer designs and operates the data infrastructure that powers product analytics, business reporting, and operational decision-making. The role owns reliable batch and streaming pipelines across application, transactional, and third-party data sources.

The Data Engineer designs and operates the data infrastructure that powers product analytics, business reporting, and operational decision-making. The role owns reliable batch and streaming pipelines across application, transactional, and third-party data sources.

You will work with analytics engineers, data analysts, software engineers, and product teams to turn complex data requirements into well-modeled, observable datasets. The team values strong data contracts, practical documentation, and systems that remain trustworthy as volume and complexity grow.

Key Responsibilities

• Design, build, and maintain batch and streaming data pipelines using Python, SQL, Apache Airflow, and cloud-native services
• Develop scalable ELT workflows that ingest data from application databases, APIs, event streams, and SaaS platforms into Snowflake, BigQuery, or equivalent warehouses
• Model curated datasets using dimensional modeling principles and dbt, with clear ownership, documentation, and downstream usage standards
• Implement data quality checks, schema validation, lineage, and monitoring to identify freshness, completeness, and accuracy issues before they affect reporting
• Optimize warehouse queries, pipeline execution, and storage patterns to improve reliability and control infrastructure costs
• Partner with analysts and stakeholders to define metrics, data contracts, and source-of-truth tables for product and business reporting
• Review code, improve testing and deployment workflows, and contribute to engineering standards for version control, CI/CD, and production operations

What We Are Looking For

• 3–8 years of experience in data engineering, analytics engineering, or a closely related software engineering role
• Strong SQL and Python skills, including experience writing maintainable transformations, tests, and production automation
• Hands‑on experience building and operating data pipelines with tools such as Airflow, Dagster, Kafka, Spark, or equivalent technologies
• Proficiency with a modern cloud data warehouse such as Snowflake, BigQuery, Redshift, or Databricks
• Experience with dbt or comparable transformation and data modeling frameworks, including dimensional modeling and incremental processing
• Bachelor's degree in computer science, engineering, mathematics, statistics, or a related technical field, or equivalent practical experience
• Bonus: experience with Terraform, Kubernetes, streaming architectures, data observability tools, and platforms such as AWS, GCP, or Azure