Deutsche Telekom Digital Labs
Data Engineering Manager
- Compensation
- Not disclosed
- Location
- Gurgaon
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Strong technical leader with hands-on engineering expertise.
- Experience building platforms handling high-volume consumer data.
- Passion for solving complex scalability and performance challenges.
- Excellent communication and stakeholder management skills.
- Proven ability to build and lead high-performing engineering teams.
- Cloud Platforms: Strong hands-on experience with AWS or GCP. Experience with cloud-native architectures.
- Data Technologies: Data Lake, Data Warehouse, ETL/ELT Pipelines, Batch & Streaming Processing, Kafka/PubSub/Kinesis, Spark, Airflow/Cloud Composer, BigQuery/Redshift/Snowflake, S3/GCS.
- Programming: Python, Java or Scala, SQL.
- Databases: PostgreSQL, MySQL, MongoDB, Cassandra (Good to have).
- DevOps: Docker, Kubernetes, Terraform, Jenkins/GitHub Actions, CI/CD.
- Monitoring: Prometheus, Grafana, CloudWatch, Datadog.
Nice to have
- Experience with real-time analytics platforms.
- Machine Learning or AI data platform exposure.
- Data governance and data quality frameworks.
- Multi-cloud architecture experience.
- Experience handling petabyte-scale data platforms.
Full description
We are looking for an experienced Engineering Manager - Data Platform to lead the design, development, and scaling of modern cloud-native data platforms. The ideal candidate should have a strong engineering background, hands-on expertise in AWS/GCP data technologies, and proven experience leading high-performing engineering teams in fast-paced B2C/D2C product organisations. This role requires a leader who can drive technical excellence, mentor engineers, and build scalable, reliable, and secure data platforms supporting millions of users.
Responsibilities:
- Lead and mentor a team of Data Engineers, Software Engineers, and Tech Leads.
- Design, develop, and scale cloud-native data platforms on AWS or GCP.
- Own architecture decisions for batch, streaming, and real-time data pipelines.
- Build highly available, fault-tolerant, and scalable data infrastructure.
- Drive engineering best practices including code quality, CI/CD, testing, observability, and automation.
- Partner with Product, Analytics, Data Science, and Business teams to deliver data-driven solutions.
- Optimise data processing performance and cloud infrastructure costs.
- Ensure platform security, governance, and compliance standards.
- Establish engineering metrics, sprint planning, and agile delivery practices.
- Hire, coach, and retain top engineering talent.
Requirements:
- Strong technical leader with hands-on engineering expertise.
- Experience building platforms handling high-volume consumer data.
- Passion for solving complex scalability and performance challenges.
- Excellent communication and stakeholder management skills.
- Proven ability to build and lead high-performing engineering teams.
- Cloud Platforms: Strong hands-on experience with AWS or GCP. Experience with cloud-native architectures.
- Data Technologies: Data Lake, Data Warehouse, ETL/ELT Pipelines, Batch & Streaming Processing, Kafka/PubSub/Kinesis, Spark, Airflow/Cloud Composer, BigQuery/Redshift/Snowflake, S3/GCS.
- Programming: Python, Java or Scala, SQL.
- Databases: PostgreSQL, MySQL, MongoDB, Cassandra (Good to have).
- DevOps: Docker, Kubernetes, Terraform, Jenkins/GitHub Actions, CI/CD.
- Monitoring: Prometheus, Grafana, CloudWatch, Datadog.
Leadership Expectations:
- 4+ years of engineering management experience.
- Managed teams of 10-20+ engineers.
- Strong stakeholder management skills.
- Experience driving large-scale engineering programs.
- Excellent people management and mentoring capabilities.
- Strong architectural and system design expertise.