Data Engineer I: Build Scalable Data Pipelines

Logoslabs; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Netomi seeks a data/analytics engineer to architect scalable pipelines and drive data-informed decisions. You will build ETL/ELT processes, perform EDA, and collaborate with data scientists and engineers to design robust data models.

Strong Python and SQL skills plus cloud data platform experience are required; a DevOps mindset and awareness of AI/ML data concerns are a plus. The role emphasizes a collaborative, agile environment with responsibilities spanning data engineering and product

Qualifications

• Bachelor’s or Master’s in CS/Engineering or related field.
• 2+ years in data engineering or backend development.
• Solid knowledge of relational databases (RDS, MySQL, PostgreSQL).
• Experience with Kafka or RabbitMQ for async systems.
• Proficiency in Python, SQL, and at least one orchestration tool (Airflow/ Luigi/ Prefect).
• Strong experience with cloud data platforms (Redshift/ BigQuery/ Snowflake/ Databricks).
• Deep understanding of data modeling and warehousing.

Responsibilities

• Architect scalable data pipelines using modern platforms (Spark, Databricks, Airflow, Snowflake).
• Develop ETL/ELT processes to ingest diverse data sources.
• Perform Exploratory Data Analysis to uncover trends and inform product decisions.
• Collaborate with data scientists, analysts, and engineers on data models.
• Write clean, tested Python code with unit/integration tests.
• Work in an agile environment and own end-to-end feature delivery.

Skills

Python

SQL

EDA

Data pipelines

Education

Bachelor's or Master's in Computer Science or Engineering

Tools

Spark

Databricks

Airflow

Snowflake

Kafka

RabbitMQ

AWS Redshift

GCP BigQuery

Databricks

Job description

Netomi seeks a data/analytics engineer to architect scalable pipelines and drive data-informed decisions. You will build ETL/ELT processes, perform EDA, and collaborate with data scientists and engineers to design robust data models.

Strong Python and SQL skills plus cloud data platform experience are required; a DevOps mindset and awareness of AI/ML data concerns are a plus. The role emphasizes a collaborative, agile environment with responsibilities spanning data engineering and product