Engineering Manager Data (AWS / GCP)
Description
Responsibilities:
- Lead and mentor Data Engineering teams, fostering a culture of innovation and technical excellence.
- Drive the design, development, and deployment of scalable cloud-based data platforms.
- Define technical architecture, engineering best practices, and coding standards.
- Collaborate with Product Managers, Architects, Data Scientists, and cross-functional teams to deliver business-critical data solutions.
- Oversee project planning, sprint execution, risk management, and timely delivery.
- Optimise data pipelines for performance, scalability, reliability, and cost efficiency.
- Ensure high availability, security, governance, and compliance across data platforms.
- Coach engineers through performance management, career development, and technical mentoring.
- Drive cloud adoption and modernisation initiatives.
- Participate in architectural reviews and strategic technology decisions.
The core requirements for the job include the following:
Cloud (Mandatory - Expertise in either one):
- Amazon Web Services (AWS) OR
- Google Cloud Platform (GCP)
Data Engineering:
- Data Lakes & Data Warehouses
- ETL/ELT Pipeline Development
- Batch & Real-Time Data Processing
- Distributed Data Processing Frameworks
- Data Modeling
- Data Governance
- Metadata Management
- Data Quality Frameworks
Big Data Technologies:
- Apache Spark
- Hadoop Ecosystem
- Kafka
- Airflow
- Hive
- Databricks (preferred)
Programming:
- Python
- SQL
- Scala or Java (preferred)
Databases:
- PostgreSQL
- MySQL
- BigQuery / Redshift
- Snowflake (preferred)
DevOps and CI/CD:
- Docker
- Kubernetes
- Terraform
- Git
- Jenkins/GitHub Actions
- Infrastructure as Code (IaC)
Leadership Expectations:
- 4+ years of Engineering Management experience.
- Experience managing teams of Data Engineers.
- Strong stakeholder management and communication skills.
- Experience delivering enterprise-scale cloud data platforms.
- Strong decision-making and problem-solving abilities.
- Agile/Scrum delivery experience.
Preferred Qualifications:
- Experience with Data Mesh or Lakehouse architecture.
- Exposure to Machine Learning data pipelines.
- Cloud certifications (AWS or GCP) are preferred.
- Experience in Telecom or large-scale enterprise environments is a plus.
Education:
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
Must-Have Skills:
- 11-14 years of experience
- Engineering Management
- Data Engineering
- AWS OR GCP (either one is mandatory)
- Python
- SQL
- Apache Spark
- Kafka
- Airflow
- ETL/ELT
- Data Warehousing
- Docker
- Kubernetes
- Terraform
- CI/CD
- Agile/Scrum
- Team Leadership
- Stakeholder Management
Skills
- Agile
- Airflow
- AWS
- Big Data
- BigQuery
- CI/CD
- Cloud
- Data Engineering
- Data Governance
- Data Lake
- Data Mesh
- Data Modeling
- Data Pipelines
- Data Quality
- Data Warehousing
- Databricks
- DevOps
- Docker
- ELT
- ETL
- GCP
- Git
- GitHub
- GitHub Actions
- Hadoop
- Hive
- Infrastructure as Code
- Java
- Jenkins
- Kafka
- Kubernetes
- Lakehouse
- Machine Learning
- Metadata Management
- MySQL
- Performance Management
- PostgreSQL
- Python
- Redshift
- Scala
- Scrum
- Snowflake
- Spark
- SQL
- Stakeholder Management
- Terraform

