Senior Software Engineer - Data Acquisition Team
ZoomInfo Technologies LLC
| Company | ZoomInfo Technologies LLC |
| Category | Engineering |
| Location | Waltham |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 10 Jul 2026 |
| Last verified | 6 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast. The Opportunity
We're looking for a Senior Software Engineer to join the Data Acquisition team - one of ZoomInfo's most strategically important
engineering areas.
In this role, you will design, build, and operate the backend systems and data pipelines that acquire, transform, validate, and
store large raw data sets from a wide range of sources. You will work across distributed processing, workflow orchestration,
streaming and batch data flows, and cloud infrastructure.
This is a senior individual-contributor engineering role focused on technical depth, production execution, and high-quality data
systems. The right candidate brings strong backend engineering fundamentals, significant pipeline experience, and the ability to
turn complex data acquisition requirements into scalable systems.
What You'll Do
- Design, build, and operate large-scale data acquisition pipelines that ingest, validate, transform, enrich, and store high-volume raw
data.
- Architect resilient ETL/ELT workflows for batch, streaming, scheduled, and event-driven data processing.
- Develop production Java services and data processing applications for ingestion, orchestration, enrichment, deduplication, and
delivery.
- Build and improve systems using technologies such as Apache Airflow, Apache Beam, Spark, Google Dataflow, DataProc, Kafka,
and Pub/Sub.
- Define practical approaches for schema evolution, data contracts, data validation, backfills, replayability, and idempotent
processing.
- Improve reliability, performance, scalability, and cost efficiency across data acquisition pipelines and services.
- Implement observability, monitoring, and alerting for pipeline health, throughput, latency, failure rates, and data quality metrics.
- Work with product, data science, platform, and data quality teams to translate business needs into production-ready systems.
- Contribute to technical designs, implementation plans, and system modernization efforts across Data Acquisition.
Must-Have Qualifications
Data Engineering and Pipelines
- 5+ years of professional software engineering experience with a strong focus on backend systems, data engineering, or distributed
processing.
- Proven experience building and operating production data pipelines at scale.
- Deep proficiency with Java and object-oriented design.
- Hands-on expertise with data processing and orchestration technologies such as Apache Beam, Apache Airflow, Spark, Google
Dataflow, or DataProc.
- Strong experience with streaming systems such as Apache Kafka, Google Pub/Sub, or similar technologies.
- Strong understanding of batch processing, streaming processing, data modeling, schema evolution, and data quality
management.
ZoomInfo - Data Acquisition Page 1 - Experience designing ETL/ELT workflows that process large volumes of structured and semi-structured data.
Backend and Distributed Systems
- Experience designing high-throughput, fault-tolerant backend services and distributed systems.
- Strong understanding of APIs, integration patterns, retries, backpressure, idempotency, and operational failure modes.
- Ability to write clean, maintainable production code and evaluate tradeoffs in system design.
- Experience with large-scale storage and query technologies such as BigQuery, Snowflake, Trino, or similar systems.
Cloud and Operations
- Experience with at least one cloud provider, preferably GCP.
- Hands-on experience with cloud services such as BigQuery, GCS, GKE, Dataflow, DataProc, and Pub/Sub.
- Experience operating production services with monitoring, loggin