Data Team Lead

1. Technical Expertise

• Cloud Data Platforms: Expertise in Google Cloud Platform (GCP) services, especially in data-related services like BigQuery, Cloud SQL, Dataproc, Pub/Sub, and Dataflow.
• Data Engineering: Strong knowledge of data pipelines, ETL/ELT processes, and data integration using GCP tools.
• Database Management: Experience with both relational and non-relational databases, including MySQL, PostgreSQL, and NoSQL solutions like Firestore or Bigtable.
• Programming Skills: Proficiency in Python, SQL, and possibly other languages like Java or Scala, with a focus on data manipulation and processing.
• APIs and Integrations: Experience working with Google APIs and third-party APIs for data extraction and integration.
• Machine Learning: Familiarity with Google Cloud AI tools, such as Vertex AI, and how to integrate machine learning workflows into the data architecture.
• Data Governance: Knowledge of data security, privacy, governance, and regulatory requirements (GDPR, HIPAA, etc.).

• Team Management: Ability to lead a team of data engineers, analysts, and architects, providing guidance, mentorship, and performance management.
• Project Management: Strong skills in managing data projects, ensuring timely delivery while meeting client requirements.
• Collaboration: Experience working cross-functionally with stakeholders such as solution architects, developers, and business teams to translate business needs into data solutions.
• Resource Allocation: Efficiently managing cloud resources to optimize cost and performance.

• Consulting: Experience in providing consulting services to clients, including understanding their data needs, providing solutions, and guiding them through the data modernization process.
• Pre-sales Support: Supporting sales teams in scoping out client projects, preparing presentations, and explaining technical aspects of data solutions during pre-sales.
• Client Relationship Management: Building and maintaining strong relationships with clients to ensure satisfaction and long-term partnership.

• Google Cloud Certifications:
• Professional Data Engineer (preferred)
• Professional Cloud Architect (preferred)
• Other Certifications: Optional certifications in data engineering or machine learning from organizations like Cloudera, AWS, or Microsoft Azure can be advantageous.
• Educational Background: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.

• Problem-Solving: Ability to troubleshoot data-related issues and implement scalable solutions.
• Adaptability: Ability to keep up with the rapidly changing cloud and data landscape.
• Communication: Excellent verbal and written communication skills to explain complex data systems to non-technical stakeholders.