[Remote] Senior Engineering Manager, Data Engineering
Note: The job is a remote job and is open to candidates in USA. Horizon3.ai is a fast-growing, remote cybersecurity company dedicated to enabling organizations to proactively find, fix, and verify exploitable attack vectors. The Senior Engineering Manager, Data Engineering will lead the team responsible for the internal data platform, driving modernization of data architecture and ensuring high-quality data access for analytics and decision-making.
Responsibilities
- Drive and lead execution on a modernization of Horizon3’s data architecture
- Define data quality and timeliness standards. Drive data quality, observability and pipeline robustness efforts to provide reliable and performant access to data to consumers
- Act as a product owner to capture needs of product teams, BI teams, and other customers and manage the roadmap of data engineering initiatives
- Grow a team of data engineers, infrastructure engineers, and data analysts. Establish a culture of collaboration and engineering excellence
Skills
- Demonstrated expertise leading teams designing and operating cloud data warehouse in production (eg, Redshift, Snowflake, Databricks, BigQuery)
- Hands-on experience with the modern data stack: dbt for transformation, a pipeline orchestrator (Airflow, Dagster, or similar), and managed ingestion tooling (Fivetran, Airbyte, etc.)
- Experience implementing data quality frameworks and observability: defining pipeline SLAs, detecting and alerting on anomalies, and establishing tiered data sets with quality guarantees (e.g., medallion architecture)
- Able to partner with and influence peer engineering teams - drive alignment on shared standards such as pipeline patterns, data contracts, and quality guarantees across teams that own their own data sources
- Experience building or significantly growing a small data engineering team — including hiring, onboarding, and establishing engineering norms
- Proven ability to define and instill engineering culture: code review standards, definition of done, incident response, documentation practices, and culture of ownership
- Drives high-impact architecture decisions rigorously — requires design documents, runs structured reviews, builds consensus, and ensures decisions are well-reasoned before commitment
- Demonstrated experience acting as product owner for a platform or infrastructure team: maintaining a roadmap, triaging inbound requests, managing internal customer expectations, and making prioritization tradeoff decisions against capacity
- Proficient in SQL. Able to read, write, and review data transforms and data quality checks in SQL
- Proficient in Python. Ability to review pipeline code and guide engineering decisions
- Competent in data analysis. Able to investigate anomalies, validate data quality issues, and find insight in data
- Familiarity with AWS data services (Redshift, Athena, S3/Glue)
- Experience with Databricks (Delta Lake, Unity Catalog, Spark)
- Familiarity with Argo Workflows or Kubernetes-native job orchestration
- Experience with high volume streaming data (Kafka, PubSub)
- Experience supporting data science or ML workflows
- Exposure to cybersecurity, network telemetry, APM, or other high-volume operational SaaS data
Benefits
- Health, vision & dental insurance for you and your family
- Flexible vacation policy
- Generous parental leave
Company Overview