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Data Engineer Leader

2 weeks ago

Bengaluru, Karnataka, India beBeeEngineering Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
About Us

We are a technology-first organization obsessed with delivering the highest standards in food quality, cold chain logistics, and customer satisfaction.

Job Overview:

We seek a seasoned leader to oversee the development and operations of our modern data and infrastructure platform. The ideal candidate will 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 experienced professionals.

Data Platform & Engineering:

- Design, build, and maintain scalable and secure data infrastructure using cloud-native 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.

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

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 8–12 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.

Requirements:

  • Bachelor's or Master's 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.

Nice to Have:

  • Experience with data privacy regulations.
  • Exposure to security best practices in DevOps and cloud infra.
  • Familiarity with Data Mesh or Lakehouse architecture.
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