Senior Data Engineer

Zoominfo; United States; Remote; USD 110,000 - 170,000; Full time

Benefits offered by this job

Remote work

Job summary

ZoomInfo is seeking a data engineer to build and operate data pipelines and transformative models that power cross-functional business initiatives. You’ll own the full delivery cycle—from clarifying stakeholder needs to deploying, monitoring, and maintaining production data assets across multiple domains.

You will develop end-to-end ingestion pipelines, build semantic-layer data models, and collaborate with teams across marketing, finance, sales, legal, HR, and product to translate data needs

Qualifications

• 4+ years of data engineering experience with production pipelines.
• Strong SQL and Python skills including production coding and debugging.
• Hands-on experience with cloud data warehouses (Snowflake preferred; BigQuery or equivalents accepted).
• Experience building and maintaining dbt models, plus Airflow and Fivetran.

Responsibilities

• Develop and own end-to-end ingestion and transformation pipelines using orchestration, connectors, modeling, and compute tools.
• Build and maintain tested, reusable data models for semantic layer and downstream dashboards/apps.
• Collaborate with marketing, finance, sales, legal, HR, and product to translate data needs into specs.
• Contribute to infrastructure-as-code and manage cloud resources and data connectors.
• Apply CI/CD, code reviews, observability, testing, and documentation practices.
• Troubleshoot pipeline and data quality issues, monitor SLAs, support incident response, protect PII.

Skills

SQL

Python

Data modeling

CI/CD for pipelines

Tools

Snowflake

BigQuery

dbt

Airflow

Fivetran

Databricks

Terraform

AWS S3

Lambda

GCP

Job description

Role overview

Build and operate data pipelines, transformation models, and infrastructure for cross-functional business initiatives. This hands-on role spans the full delivery cycle, from clarifying stakeholder needs and selecting suitable tools to deploying, monitoring, and maintaining production data assets across multiple business domains.

Responsibilities

• Develop and own end-to-end ingestion and transformation pipelines, using orchestration, connector, modeling, and custom compute tools as appropriate.
• Build and maintain tested, documented, reusable data models that support a semantic layer and downstream dashboards or internal applications.
• Work with teams across marketing, finance, sales, legal, human resources, and product to scope data needs and translate them into technical specifications.
• Contribute to infrastructure managed as code, including cloud resources and data connectors.
• Apply team practices for version control, CI/CD, code review, observability, testing, and documentation.
• Troubleshoot complex pipeline and data quality issues, monitor service commitments, support incident response, and protect personal data under relevant access and compliance requirements.

Requirements

• At least four years of data engineering experience, including ownership of production pipelines.
• Strong SQL and Python skills, including production coding, debugging, and query optimization.
• Hands-on experience with a cloud data warehouse; Snowflake is preferred, with BigQuery or an equivalent accepted.
• Production experience building and maintaining dbt models, plus experience with Airflow and Fivetran.
• Experience with Databricks and Spark, AWS services such as S3 and Lambda, and GCP services such as BigQuery.
• Ability to take ambiguous requests from initial scoping through delivery with limited oversight, and explain tradeoffs clearly to nontechnical partners.
• Familiarity with CI/CD for data pipelines, team dbt projects, infrastructure-as-code tools, PII handling, and access controls.

Nice to have

• Experience with Dagster or a comparable orchestration tool.
• The ability to combine broad end-to-end engineering skills with deeper expertise in selected areas.

Benefits and work setup

• The listing identifies the position as remote. The data platform includes Snowflake and BigQuery, Fivetran, Airflow, dbt, Databricks, Terraform, AWS, GCP, GitHub, and Tableau.