Senior Data Engineer: Data Lake, Graph & GenAI Ops

Worldly; United States; Remote; USD 135,000 - 165,000; Full time

Benefits offered by this job

Annual bonus 10%

Stock options

Work-from-home stipend

Fully paid parental leave

Unlimited PTO

12 paid company holidays

Medical, dental, and vision coverage (

60% spousal/dependent premiums)

Job summary

worldly is seeking a senior hands-on data engineer to build and operate the analytics backbone powering internal insights and customer-facing products. You will own a CDC-fed medallion data lake, a Postgres warehouse, and the integration of a graph database while extending production generative AI workflows.

The role requires 5+ years in data engineering with advanced SQL, Postgres, Python, and experience with Iceberg, Trino, dbt, and Dagster/Airflow.

Qualifications

• 5+ years in data engineering, analytics engineering, or data platform engineering.
• Advanced SQL and relational database experience with Postgres and MongoDB, plus hands-on production graph database experience.
• Experience with open table formats and medallion architectures such as Apache Iceberg, distributed SQL engines like Trino or Presto, and streaming or CDC pipelines (e.g., Kafka, Debezium, Flink).
• Strong Python skills for pipelines and automation, plus experience using dbt orchestrated by a modern scheduler like Dagster or Airflow.
• AWS infrastructure experience via infrastructure-as-code such as Terraform, along with CI/CD, GitOps, and Docker.
• Background in analytics data modeling, metric definitions, automated monitoring, and data security practices.

Responsibilities

• Own the production data lake end-to-end, including CDC ingestion, medallion layers on Apache Iceberg, the Trino query layer, and the table catalog.
• Operate and evolve the Postgres data warehouse, including schema design, performance tuning, and access controls.
• Integrate the graph database with the warehouse, lake, and primary databases, migrating legacy pipelines onto a single governed integration layer.
• Maintain and evolve Dagster-orchestrated dbt pipelines with sensor-triggered builds, data quality tests, and branch-based versioning.
• Operate the BI and reporting layer, enforcing per-user policy-based data access at the query engine rather than only at the dashboard.
• Support and extend production genAI workflows such as embeddings, similarity search, and LLM-based extraction and classification.

Skills

Advanced SQL

Postgres

MongoDB

Graph databases

Python

dbt

Dagster

Airflow

Terraform

Docker

Kafka

Debezium

Flink

Trino/Presto

Iceberg

Data modeling

Data security

Tools

Dagster

Airflow

Terraform

Docker

Kafka

Debezium

Flink

dbt

Trino

Presto

Iceberg

Postgres

MongoDB

Job description

worldly is seeking a senior hands-on data engineer to build and operate the analytics backbone powering internal insights and customer-facing products. You will own a CDC-fed medallion data lake, a Postgres warehouse, and the integration of a graph database while extending production generative AI workflows.

The role requires 5+ years in data engineering with advanced SQL, Postgres, Python, and experience with Iceberg, Trino, dbt, and Dagster/Airflow.