Software Engineer III - Analytical Data

ZoomInfo Technologies LLC • Bethesda, MD

4d • $112,000 - $176,000 • Hybrid

About The Position

ZoomInfo is hiring a Software Engineer III for its Analytical Data team, which builds and operates the lakehouse for ZoomInfo’s Data organization. The team is creating a governed source of people and company data, written as Apache Iceberg tables and stored on Google Cloud Storage and Amazon S3. The data is queried in place through BigQuery, Snowflake, and Starburst/Trino, so teams and AI agents can access fresh, trusted datasets without separate copies or export pipelines.

This hands-on data engineering role spans streaming and batch ingestion, Iceberg table management, access across multiple query engines, data contracts with producer teams, and observability. The datasets may contain hundreds of millions of records and are mostly refreshed daily. The engineer will own production pipelines, collaborate with data consumers and platform teams, and help shape the platform’s technical roadmap.

Requirements

• At least 3 years of professional software engineering experience, focused on data engineering or distributed systems.
• Strong programming skills in Kotlin, Java, or Python; the role involves working in Kotlin and Python.
• Hands-on experience with Apache Beam, ideally on Google Cloud Dataflow, or Apache Spark.
• Production pipeline experience with Apache Kafka or a similar streaming platform.
• Experience with very large datasets and distributed systems, including designing efficient data models and storage layouts.
• Understanding of lakehouse architecture and open table formats; Apache Iceberg is preferred.
• Strong SQL skills and working knowledge of at least one of BigQuery, Snowflake, or Starburst/Trino.
• Experience with Protobuf or Avro schemas and evolving schemas without breaking downstream consumers.
• Experience with GCP or AWS; the environment is GCP-first and also uses AWS for storage and catalogs.
• Understanding of the SDLC for data pipelines, including unit, integration, and end-to-end testing.
• Experience operating production pipelines with metrics, dashboards, and alerts, and taking end-to-end responsibility for production incidents.
• Practical everyday use of AI coding assistants such as Claude Code or Codex, with the judgment to review and test their output.
• Cross-team collaboration experience, including working with producer teams on schema changes and with data consumers and platform or infrastructure teams.
• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
• Pragmatic engineering judgment and ability to balance quality, speed, and business impact.

Nice To Haves

• Production experience with Apache Iceberg, including table maintenance, partition and schema evolution, and catalogs such as BigLake metastore, AWS Glue, or Project Nessie.
• Experience with metadata catalogs and data governance tooling such as OpenMetadata.
• Experience building AI agents that monitor pipelines, triage alerts, or investigate data issues.
• Experience serving the same data to multiple query engines or running data infrastructure across GCP and AWS.
• Experience negotiating data contracts between producer and consumer teams.
• Experience contributing to technical strategy or a roadmap for data processing infrastructure.
• Experience with Terraform, Apache Airflow (Cloud Composer), or dbt.

Responsibilities

• Build and operate Kotlin and Apache Beam pipelines on Google Cloud Dataflow to load data from Kafka and cloud storage into Apache Iceberg tables.
• Maintain large Iceberg tables for correctness, performance, and cost efficiency through partitioning and Spark maintenance jobs, including compaction, deduplication, snapshot expiry, and orphan-file cleanup.
• Reconcile lakehouse data against its source.
• Make datasets queryable from BigQuery, Snowflake, and Starburst/Trino through Iceberg catalogs and stable consumer views.
• Work with producer teams on schemas and data contracts, and make publishing new datasets simple and documented.
• Build observability for dataset freshness, completeness, and budget, including Datadog dashboards and monitors, with plans for AI agents to assist with alert triage.
• Own production pipelines end to end, including incident response and corrective fixes.
• Ship through code review, CI/CD, staged releases, and unit, integration, and end-to-end testing.
• Manage infrastructure in Terraform across GCP and AWS.
• Work with data consumers, producer teams, and platform teams, and contribute to the platform’s technical roadmap.

Benefits

• Comprehensive benefits.
• Holistic mind, body, and lifestyle programs designed to support overall well-being.
• Additional compensation such as bonus, commission, and equity may apply.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level