Lead Consultant, Data Architecture & Engineering
T
TASQ Staffing SolutionsData architecture
Source API remote eligibility restrictions: PhilippinesFull-TimeLead
SalaryCompetitive compensation package, salary, allowance, standard benefits including quarterly and annual performance-based cash bonuses, and other remuneration.
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Job Details
- Experience
- At least 4 years of relevant leadership experience
- Required Skills
- PythonSQLRESTful APIsData modelingPySpark
Requirements
- Have at least 4 years of relevant leadership experience.
- Have experience leading small- to medium-sized technical teams, including work allocation, technical escalation, and support.
- Have expertise designing and implementing logical and physical data models for cloud and hybrid data warehouse environments.
- Have experience implementing data architectures for structured, semi-structured, and unstructured data.
- Have experience with multiple full life-cycle data warehouse implementations.
- Understand data architectures for data integration processing.
- Have experience with data modeling technologies such as ER/Studio, ER/Win, or similar.
- Have experience with Microsoft Azure Data Platform services, including Azure Data Lake Store, Azure Storage, Azure Synapse, Azure Data Factory, Azure SQL Database, Logic Apps, and APIs.
- Have Python and SQL scripting skills, including SQL and PySpark.
- Have general cloud architecture skills and the ability to build data pipelines from requirements.
- Have API knowledge; ability to create APIs is preferred.
- Be able to learn, adopt, and apply new technologies quickly.
Responsibilities
- Lead small- to medium-sized technical teams, including allocating and distributing work.
- Provide technical escalation and support to team members.
- Represent the team in Agile ceremonies and client meetings.
- Make technical decisions and guide and mentor junior team members.
- Design and implement logical and physical data models for cloud and hybrid data warehouse environments.
- Implement data architectures that support structured, semi-structured, and unstructured data.
- Build data pipelines and architectures that support data integration processing.
- Profile data and create source-to-target mappings.
- Provision and configure Azure data service resources.
- Develop relationships with project, client, and company leadership while remaining hands-on.
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