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.