Manager, Data Platform
Leads strategy, architecture, operations, and modernization of an enterprise data platform while managing and mentoring data platform engineers. Requires 8+ years in data engineering, platforms, or architecture and experience with production cloud data systems.
About the job
Responsibilities
Technical Strategy & Architecture
- Define and evolve the vision, roadmap, and technical strategy for the data platform.
- Own architecture across ingestion, transformation, orchestration, storage, serving, governance, and observability.
- Establish engineering standards for pipelines, data contracts, infrastructure, and deployment.
- Evaluate technologies, vendors, and architectural approaches with stakeholders.
- Remain hands-on in architecture reviews, prototyping, critical initiatives, and complex troubleshooting.
People Leadership & Management
- Manage, mentor, and develop a team of data platform engineers.
- Set expectations for technical execution, ownership, collaboration, and operational excellence.
- Support career growth through feedback, coaching, and performance management.
- Participate in hiring, onboarding, interviewing, and capacity planning.
- Partner with leadership on team structure, priorities, and capability needs.
Platform Delivery & Operations
- Oversee reliable, scalable data pipelines and workflows.
- Establish service-level objectives, data quality standards, monitoring, alerting, and incident response practices.
- Drive platform migrations and modernization with incremental delivery and risk reduction.
- Reduce operational toil through automation, self-service capabilities, and standardized infrastructure.
Security, Governance & Data Contracts
- Establish access controls, data protection mechanisms, and security practices for sensitive data.
- Define and promote data contracts and ownership boundaries between source systems, platforms, and consumers.
- Improve data discoverability, lineage, and trust.
- Support secure access for analytics, machine learning, and AI workloads.
Collaboration
- Partner with application engineering, analytics engineering, data science, product, security, and infrastructure teams.
- Translate stakeholder needs into technical requirements and prioritized initiatives.
- Communicate architectural decisions, tradeoffs, and progress to technical and non-technical audiences.
Requirements
- 8+ years of experience in data engineering, data platforms, or data architecture.
- 2+ years managing, mentoring, or leading data engineering teams.
- Experience designing and operating production-grade data platforms and cloud architectures.
- Strong experience with data orchestration, transformation frameworks, and pipeline development.
- Strong understanding of data security, access controls, governance, and data contracts.
- Ability to balance hands-on technical contribution with people leadership.
- Excellent written and verbal communication skills.
Nice-to-Haves
- Experience with AWS services including Redshift, S3, IAM, EKS, Glue, ECR, and DMS.
- Experience with Python, SQL, Airflow, dbt, and infrastructure as code.
- Experience supporting machine learning platforms, LLM/AI access, or production ML services.
- Experience building or managing data contracts, semantic layers, or data interfaces.
Compensation & Benefits
- Base salary: $140,000–$220,000 USD.
- Additional compensation such as bonus, commission, equity, and other benefits may apply.
- Comprehensive benefits and holistic mind, body, and lifestyle programs.
Skills
Databricks, Snowflake, AWS, Spark, dbt, Fivetran, Apache Airflow, BigQuery, Python, SQL, Infrastructure As Code, Data Governance, Data Contracts, Machine Learning
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