Data Architect (Data Modeling & ETL Specialization)

Role Summary
As a Data Architect at Project X Ltd., you will be providing our clients with your knowledge and experience in making sense of messy, unstructured data. The Data Architect will be responsible for designing, implementing, and overseeing end-to-end solutions that address designing scalable and efficient data solutions, and complex business challenges and unlock the value of data for our clients.

Major Areas of Responsibility

Data Strategy and Architecture:

• Define and execute data strategies that align with clients' business objectives and support their digital transformation initiatives.
• Lead the development of enterprise-wide data architectures, including conceptual, logical, and physical data models, data flows, and integration patterns.

Data Governance and Compliance:

• Establish and enforce data governance policies, standards, and best practices to ensure data quality, integrity, and security.
• Ensure compliance with regulatory requirements such as GDPR, CCPA, HIPAA, and industry-specific standards.

Data Integration and Migration:

• Lead the design and implementation of data integration solutions to consolidate, transform, and migrate data from disparate sources.
• Architect data pipelines and orchestration workflows using modern integration technologies and platforms.

Advanced Analytics and Machine Learning:

• Collaborate with data scientists and analytics teams to design and implement advanced analytics solutions, including predictive modeling and machine learning algorithms.
• Architect data lakes and analytical environments to support exploratory data analysis and data science initiatives.

Cloud Data Platform and Big Data Solutions:

• Design and implement scalable and cost-effective data architectures on cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Architect big data solutions leveraging technologies such as Hadoop, Spark, Kafka, and NoSQL databases.

Data Visualization and Insights Delivery:

• Develop interactive dashboards, reports, and visualizations to deliver actionable insights and key performance indicators (KPIs) to stakeholders.
• Utilize data visualization tools such as Power BI, Tableau, or Looker to create compelling and intuitive visualizations.

Client Engagement and Thought Leadership:

• Serve as a trusted advisor to clients, providing strategic guidance, technical expertise, and thought leadership on data architecture and analytics topics.
• Lead client workshops, training sessions, and presentations to evangelize data-driven decision-making and promote best practices.

Required Knowledge, Skills, Abilities and Other

• College, Bachelor's, or Master's degree in Computer Science, Information Systems, or a related field.
• Deep understanding of cloud computing principles and experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud Platform)
• 5+ years of experience in data architecture, data engineering, and analytics, with a focus on enterprise-scale solutions.
• Proven track record of designing and implementing complex data architectures and solutions across multiple industries and domains.
• Expertise in data modeling, database design, and optimization techniques, with hands-on experience in relational and NoSQL databases.
• Strong programming skills in languages such as SQL, Python, or Scala, with experience in data manipulation, transformation, and analysis..
• Excellent communication, presentation, and stakeholder management skills, with the ability to effectively communicate technical concepts to non-technical audiences.
• Strong leadership and team management skills, with the ability to mentor junior team members and lead cross-functional project teams.

Nice to Have:

• Certification in relevant technologies or methodologies (e.g., AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect Expert, Certified Data Management Professional).
• Experience with data governance frameworks, metadata management tools, and data catalog solutions.
• Knowledge of emerging trends and technologies in data architecture, such as data mesh, event-driven architectures, and streaming analytics.

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