Senior Engineering Manager, Data Platform
New
G
Galileo Financial Technologies LLCFintech
US - Remote (Contingent Worker); CA - Remote; WA - Seattle; UT - Cottonwood Heights; CA - San Francisco; NY - New York CityFull-TimeManager
Salary$172,800.00 - $297,000.00
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Job Details
- Experience
- 8+ years in data engineering, infrastructure, or a related field, including 5+ years directly managing engineers or analysts
- Required Skills
- AWSApache AirflowKafkaSnowflakeData engineeringTerraformBigQuerydbtRedshift
Requirements
- 8+ years in data engineering, infrastructure, or a related field.
- 5+ years directly managing engineers or analysts, including leading teams of 6+ or managing leads.
- Proven experience owning data platforms end-to-end: pipelines, warehousing, and orchestration (e.g., Airflow, dbt).
- Strong knowledge of modern cloud data warehousing such as Snowflake, BigQuery, or Redshift.
- Proficiency with cloud infrastructure and IaC, specifically AWS and Terraform.
- Experience with streaming and ingestion tooling like Kafka, DMS, or Flink.
- Familiarity with security and compliance frameworks (PCI, SOC2).
- Track record of building or scaling a data team, including hiring and mentoring.
- Ability to operate in a regulated fintech environment and navigate matrixed stakeholder relationships.
- Strong systems thinking with the ability to balance build-vs-buy and short-term delivery vs. long-term platform health.
Responsibilities
- Own hiring, onboarding, and career development for the Data Platform and Data Analytics teams.
- Set technical direction and engineering standards for data pipelines, warehousing, and analytics tooling.
- Manage team roadmap, prioritization, and delivery against business goals.
- Own the architecture and reliability of the data platform, including ingestion, ETL/ELT, orchestration, storage, and serving layers.
- Extend data governance, access control, and PII/PCI-compliant handling practices.
- Partner with business stakeholders like Finance, Risk, and Product to translate needs into scalable data models and self-serve tooling.
- Oversee dashboards, metrics layers, and semantic models while championing data quality.
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