- Lead the design and implementation of scalable data solutions on GCP.
- Define data architecture, data models, and enterprise data integration strategies.
- Establish data engineering best practices, coding standards, and governance frameworks.
- Provide technical guidance and mentorship to data engineers and developers.
Data Engineering & Development
- Design and develop data pipelines using GCP services such as:
- BigQuery
- Dataflow
- Dataproc
- Pub/Sub
- Cloud Composer
- Cloud Storage
- Cloud Functions
- Build and optimize ETL/ELT processes for batch and real-time data processing.
- Implement data quality, validation, and monitoring frameworks.
Support & Operations
- Manage production support activities and incident resolution.
- Perform root cause analysis and implement preventive measures.
- Monitor platform performance, availability, and cost optimization.
- Ensure compliance with SLAs and operational excellence standards.
Stakeholder Management
- Collaborate with business stakeholders, architects, and project managers.
- Translate business requirements into scalable technical solutions.
- Drive technical discussions, architecture reviews, and solution recommendations.
- Prepare status reports and communicate project progress to leadership.
Data Governance & Security
- Implement data security controls and compliance requirements.
- Ensure adherence to data governance policies.
- Manage access controls, encryption, and auditing mechanisms.
- Team leadership and mentoring
- Stakeholder management
- Resource planning and estimation
- Agile/Scrum delivery model
Preferred Qualifications
- Bachelor's or Master's Degree in Computer Science, IT, Engineering, or related field.
- Google Cloud Qualified Data Engineer Certification.
- Experience in cloud migration and modernization programs.
- Experience working in Banking, Financial Services, Insurance, Retail, or Healthcare domains is preferred.
Experience Requirements
- 10+ years in Data Engineering/Data Warehousing.
- 5+ years of hands-on experience in GCP Data Platform implementations.
- Experience leading teams of 5+ data engineers.
- Experience managing production support and enhancement projects.
Nice to Have
- Spark/PySpark
- Kafka
- Looker
- Tableau
- Power BI
- Machine Learning and AI/ML integration on GCP
- Data Governance tools such as Collibra or Alation