Senior Data Engineer: Data Lakes, ETL & Analytics

Thrive Market; Los Angeles (CA); On-site; USD 165,000 - 190,000; Full time

Benefits offered by this job

Health benefits

401(k) plan

Stock options

Flexible PTO

Office in Playa Vista

Job summary

Thrive Market in Los Angeles, CA is seeking a Senior Data Engineer to power our data platform used by millions of members. You will own end-to-end data pipelines, from ingestion to reporting, and collaborate with the Data Strategy Team to turn data into product insights.

The role requires hands-on Python, DBT and Airflow skills, strong SQL with Snowflake, and experience building scalable data lakes and warehouses in cloud environments.

Qualifications

• Hands-on experience programming in Python, DBT and Airflow.
• Strong SQL and data warehousing knowledge (Snowflake or similar).
• Experience with data lake/warehouse architectures and data pipelines.
• Familiarity with Terraform for infrastructure as code.
• Experience with streaming data technologies (Kafka, AWS Kinesis).

Responsibilities

• Own end-to-end data services from ingestion to delivery for reporting.
• Collaborate with cross-functional teams to deliver cohesive data solutions.
• Define requirements and implementation details for data lake, warehouse, and marts.
• Identify and resolve data integrity and performance issues in production.
• Develop enterprise data architecture patterns and data model standards.
• Design pilots/POC to validate data scenarios and roadmap implementation.
• Ensure scalability, security, and reliability of data engineering solutions.
• Maintain documentation of data architecture artifacts and procedures.

Skills

Python

DBT

Airflow

SQL

Snowflake

Data Warehousing

ETL

Kubernetes

GitHub

Jenkins

Kafka

AWS Kinesis

Terraform

Spark

Tools

Terraform

GitHub

Jenkins

Kafka

AWS Kinesis

Snowflake

Spark

Airflow

Job description

Thrive Market in Los Angeles, CA is seeking a Senior Data Engineer to power our data platform used by millions of members. You will own end-to-end data pipelines, from ingestion to reporting, and collaborate with the Data Strategy Team to turn data into product insights.

The role requires hands-on Python, DBT and Airflow skills, strong SQL with Snowflake, and experience building scalable data lakes and warehouses in cloud environments.