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Senior Engineering Manager, Data Engineering
Horizon3.ai. Lead the team that provides the internal data platform that powers analytics and operational decision-making across Horizon3 .
Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSBigQueryCloudCyber SecurityKafkaKubernetesPythonSparkSQLUnity
About the role
Key responsibilities & impact- Lead the team that provides the internal data platform that powers analytics and operational decision-making across Horizon3
- 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.
Requirements
What you’ll need- 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
Comp & perks- Health, vision & dental insurance for you and your family
- Flexible vacation policy
- Generous parental leave
- Equity package in the form of stock options
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
cloud data warehouseRedshiftSnowflakeDatabricksBigQuerydbtAirflowFivetranSQLPython
Soft Skills
team leadershipcollaborationinfluenceengineering cultureproduct ownershiproadmap managementdecision makingcommunicationproblem solvingdata analysis