Engineering Manager - Data (GCP / Azure)

We are looking for an experienced Engineering Manager - Data Engineering to lead the design, development, and delivery of scalable, secure, and high-performance data platforms and solutions. The ideal candidate will have strong hands-on expertise in Google Cloud Platform (GCP) and/or Microsoft Azure, modern data engineering technologies, and proven experience managing and mentoring high-performing engineering teams. This role requires a strong combination of technical leadership, people management, architecture, and delivery ownership.
Responsibilities:
Lead and manage a team of Data Engineers, providing technical guidance, mentoring, and career development.
Define the technical vision, architecture, and roadmap for scalable enterprise data platforms.
Design and build robust batch and real-time data pipelines using modern cloud technologies.
Drive the adoption of best practices around data engineering, data quality, security, governance, and observability.
Architect and implement cloud-based data solutions on GCP and/or Azure.
Work closely with Product, Engineering, Analytics, Data Science, and Business teams to translate requirements into scalable technical solutions.
Ensure high availability, scalability, reliability, and performance of data platforms.
Drive engineering excellence through code reviews, design reviews, testing, CI/CD, and automation.
Manage project planning, execution, resource allocation, risks, and delivery timelines.
Establish reusable frameworks, standards, and best practices across the Data Engineering organisation.
Drive cloud modernisation and migration initiatives involving data platforms and applications.
Collaborate with senior leadership and stakeholders on technology strategy and execution.
Requirements:
12-17 years of overall experience in Software Engineering and Data Engineering.
Minimum 3-5 years of experience leading and managing Data Engineering teams.
Strong hands-on experience with GCP and/or Azure cloud platforms.
Experience designing and building large-scale, distributed data platforms.
GCP Experience:
Strong experience with technologies such as:
BigQuery
Cloud Storage
Dataflow
Dataproc
Pub/Sub
Cloud Composer
Cloud Functions / Cloud Run
IAM and cloud security
Azure Experience:
Experience with technologies such as:
Azure Data Factory (ADF)
Azure Databricks
Azure Data Lake Storage (ADLS)
Azure Synapse Analytics
Event Hubs / Service Bus
Azure Functions
Microsoft Fabric (preferred)
Technical Skills:
Strong programming experience in Python, Java, or Scala.
Strong expertise in SQL and data modelling.
Hands-on experience with Apache Spark and distributed data processing.
Experience building ETL/ELT pipelines and data integration solutions.
Good understanding of streaming technologies such as Kafka, Pub/Sub, or Event Hubs.
Experience with workflow orchestration tools such as Airflow / Cloud Composer.
Knowledge of modern Data Lake, Data Warehouse, and Lakehouse architectures.
Experience with CI/CD, DevOps, Infrastructure as Code, and automation.
Hands-on experience with tools such as Terraform or equivalent IaC frameworks.
Strong understanding of data security, governance, access management, and compliance.
Leadership Expectations:
Proven experience managing and scaling engineering teams.
Ability to balance hands-on technical involvement with people and delivery management.
Strong stakeholder management and communication skills.
Experience working in Agile/Scrum environments.
Ability to drive technical decisions and influence architecture across multiple teams.
Strong problem-solving and decision-making abilities.
Preferred Qualifications:
Experience working on large-scale enterprise or product-based data platforms.
Experience with multi-cloud or cloud migration initiatives.
Knowledge of Data Mesh, Data Fabric, or modern data platform architecture.
Experience supporting Data Science, Machine Learning, or AI workloads.
Cloud certifications in GCP and/or Microsoft Azure will be an added advantage.

Experience
12-16 yrs