
Manager - Data Platform
2 weeks ago
Role Overview :
We are seeking a Manager Data Platform Engineering to lead a high-performing team of data engineers and platform developers. The ideal candidate combines strong people leadership with deep technical expertise in cloud-native data infrastructure, ETL pipelines, IaC, DevOps, and unstructured data lake design. This role reports into senior technical leadership and contributes directly to product evolution and platform scalability.
Your Responsibilities :
Leadership & Team Development :
- Lead, coach, and grow a team of 8- 12 Data Engineers and Platform Engineers.
- Conduct performance reviews, career development planning, and mentoring.
- Align team efforts with product roadmap and business objectives.
- Foster a strong engineering culture around ownership, collaboration, and innovation.
Engineering Execution :
- Architect and scale data platform infrastructure, ensuring it supports growth, security, and performance expectations.
- Guide development of scalable ETL/ELT pipelines, real-time streaming data integrations (Kafka), and unstructured data lake solutions.
- Promote Infrastructure-as-Code (IaC) using tools like Terraform or CloudFormation.
- Work closely with DevOps to integrate CI/CD pipelines, enable automation, and maintain containerized environments using Docker and Kubernetes.
- Ensure full adherence to security, governance, and regulatory requirements (GDPR, SOC2, etc.).
Strategic Collaboration :
- Act as a key liaison between engineering and cross-functional partners including Product Management, Architecture, QA, UX, and DevOps teams globally.
- Collaborate on planning, prioritization, release readiness, and roadmap alignment.
- Manage risks, dependencies, and communicate updates to leadership.
Quality & Process Management :
- Ensure team delivers high-quality, well-tested, and secure data solutions.
- Implement coding standards, technical documentation, and continuous improvement practices.
- Track sprint velocity, monitor OKRs, and lead post-mortems when needed.
Required Qualifications :
- 10- 15 years of total experience in data engineering, platform engineering, or cloud architecture.
- 3+ years of experience leading high-performing teams in a cloud-native, fast-paced product organization.
- Strong technical skills with :
1. Cloud & Data Infrastructure : AWS (S3, Redshift, Glue, Lambda, EMR), Kafka
2. Languages & Tools : Python, SQL, dbt, Terraform (or similar), Docker, GitHub Actions, Jenkins
3. Data Platforms : Snowflake, Airflow, Lakehouse Architecture
- Unstructured Data : Experience working with queryable unstructured data lake stores
- Familiarity with CI/CD pipelines, containerization, and cloud cost optimization.
- Experience with multi-tenant SaaS platforms or global enterprise data environments.
Nice to Have :
- Prior experience working in regulated industries or on platforms with high data privacy requirements.
- Exposure to data governance frameworks and modern data stack technologies.
- Agile methodology expertise with tools like Jira, Confluence, and GitLab.
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