About Licious :

Licious is Indias leading D2C fresh meat and seafood brand, revolutionizing the way meat is sourced, processed, and delivered.

Were a technology-first company obsessed with ensuring the highest standards in food quality, cold chain logistics, and customer delight.

Role Overview :

We are looking for a seasoned Data Platform & DevOps Engineering Manager to lead the development and operations of our modern, cloud-native data and infrastructure platform.

Youll drive the architecture and execution of large-scale data processing, analytics systems, and DevOps practices that enable high-quality insights and rapid product iteration.

This is a strategic and hands-on leadership role, managing a team of data engineers, DevOps specialists, and cloud platform engineers.

Key Responsibilities :

Data Platform & Engineering :

- Architect, build, and maintain scalable and secure data infrastructure using tools like Apache Hadoop, Hive, Spark, Kafka, Airflow, and Delta Lake.

- Develop robust ETL/ELT pipelines, data models, and streaming data workflows to support analytics, business intelligence, and machine learning use cases.

- Optimize data storage and compute using cloud-native solutions (AWS S3, Redshift, EMR, Glue, Athena, etc.

- Integrate with modern data stack tools such as dbt, Snowflake, BigQuery, and Fivetran (or custom connectors).

- Ensure data quality, lineage, cataloging, and observability using tools like Apache Atlas, Great Expectations, and Amundsen.

- Collaborate closely with Product, Engineering, and Data Science teams to deliver accurate, timely, and actionable data.

ML & Advanced Analytics Enablement :

- Support Data Science and AI/ML teams by maintaining model pipelines and training infrastructure.

- Enable MLOps frameworks using MLflow, SageMaker, PyTorch, or TensorFlow for seamless experimentation and deployment.

- Manage model versioning, metadata tracking, and real-time inference workflows.

DevOps & Platform Engineering :

- Lead the design and implementation of robust CI/CD pipelines, version control, testing, and deployment practices.

- Implement Infrastructure as Code (IaC) using Terraform, Ansible, or Pulumi.

- Manage containerization and orchestration platforms like Docker, Kubernetes (EKS preferred).

- Own cloud infrastructure (preferably AWS), including networking, security, cost governance, and compliance.

- Set up monitoring and alerting using Prometheus, Grafana, ELK Stack, or DataDog.

Leadership & People Management :

- Hire, coach, and mentor a team of 812 data, devops and platform engineers.

- Set clear objectives, track performance, and build a culture of ownership, continuous learning, and innovation.

- Collaborate cross-functionally to translate business needs into scalable engineering solutions.

Required Skills & Qualifications :

- Bachelors or Masters degree in Computer Science, Engineering, or a related field.

- 10+ years of experience in data engineering, DevOps, or infrastructure roles, with at least 3 years in a technical leadership or managerial capacity.

- Strong experience with cloud platforms (AWS preferred), distributed data systems, and large-scale batch + real-time data processing.

- Hands-on proficiency with tools like Kafka, Airflow, Hadoop, Hive, Spark, dbt, PyTorch, MLflow, and Docker/Kubernetes.

- Proven experience in building and maintaining enterprise data platforms and ML Ops pipelines.

- Strong understanding of CI/CD, GitOps, system monitoring, SRE, and cost optimization best practices.

- Exceptional problem-solving skills, stakeholder communication, and team leadership.

- Ensure platform security, data protection compliance, and cloud infra governance.

Incident Management / SRE Practices :

- Own platform reliability, incident management processes, incident retros, and on-call practices.

Infra Scale & Optimization Responsibilities:

- Plan for infra scaling and performance benchmarking to support growing order volumes and data ingestion rates.

- Operational KPIs/OKRs will include Own infra uptime , pipeline latency , model deployment TAT , cloud cost optimization & Elevate Security & Privacy Management.

Nice to Have :

- Experience with data privacy regulations (GDPR, SOC2, etc.

- Exposure to security best practices in DevOps and cloud infra.

- Familiarity with Data Mesh or Lakehouse architecture.