Data Architect - remote

Remote contract opportunity for a Senior Data Architect with robust experience in SaaS platform data migrations and cloud data architectures like DataBricks or Snowflake. The Enterprise Data Architect is responsible for designing, implementing, and maintaining the overall data architecture of the organization. This role involves creating a comprehensive data strategy to support the business's strategic goals, ensuring data consistency, integrity, and availability across various systems.

Needs experience with:

• SaaS Data transformation and migration
• Cloud Data Platforms
• The ideal candidate will have extensive experience in data architecture, data modeling, and data management, with a strong understanding of business intelligence (BI), data analytics, lakehouse architectures, and technology.

Key Roles & Responsibilities: Data Strategy Development:

• Develop and execute the enterprise data architecture strategy aligned with the organization's goals.
• Collaborate with business leaders to understand data needs and ensure the architecture supports business objectives.
• Evaluate and recommend data management tools and technologies that align with the organization's strategic vision.
• Implement master data management, reference data management, metadata management strategies to ensure data consistency, quality and security.

Data Governance and Compliance:

• Develop and Implement data governance policies and standards, as well as performance indicators and quality metrics, to manage data effectively and ensure compliance with data-related policies and standards.
• Monitor data quality and performance metrics, addressing issues as they arise to maintain data integrity.

Architectural Design:

• Design and implement data models, data flows, and data integration strategies to support business processes.
• Develop and maintain comprehensive data architecture documentation, including data models, data dictionaries, and metadata.
• Establish data governance frameworks and best practices to ensure data quality, consistency, and security.

Lakehouse Architecture:

• Design and implement lakehouse architectures that combine the features of data lakes and data warehouses, optimizing for both structured and unstructured data.
• Utilize lakehouse platforms and tools to integrate, store, and analyze large volumes of data efficiently.
• Evaluate and recommend lakehouse solutions and technologies, including Delta Lake, Apache Hudi, MS Fabric, Databricks, or Apache Iceberg, to enhance data processing and analytics.

Business Intelligence (BI) Integration:

• Design and implement BI architecture to support reporting, analytics, and decision-making processes.
• Develop and maintain BI data models, dashboards, and reports that provide actionable insights to business stakeholders.
• Evaluate and recommend BI tools and technologies to enhance data visualization and analysis capabilities.

Collaboration and Leadership:

• Lead cross-functional teams to drive data-related projects and initiatives.
• Communicate data architecture strategies and solutions to stakeholders at all levels, including executives.
• Mentor and provide guidance to junior data architects and data management staff.

• Knowledge and expertise with enterprise systems data and data governance practices; Data-driven sales and marketing strategy; FP&A data; Cloud data architecture technology tools and platforms such as DataBricks/snowflake, DBT, Cloud ELT such as FiveTran.
• Problem Solving: Describe the nature and complexity of the problems this position encounters on a recurring basis. Include information regarding the level of innovation required, if any, and include mention of environmental factors that may add to the complexity of resolving issues.
• Data Modeling: Proficiency in data modeling techniques and tools (e.g., Erwin, IBM InfoSphere Data Architect).
• Databases: Deep knowledge of relational databases (e.g., SQL Server, Oracle) and NoSQL databases (e.g., MongoDB, Cassandra).
• Data Governance: Experience with data stewardship controls as well as observation and data cleansing technologies.
• Big Data Technologies: Familiarity with big data platforms and technologies (e.g., Hadoop, Spark) is a plus.
• Cloud Platforms: Experience with cloud-based data solutions (e.g., AWS S3, Azure, Google, etc) and architectures.
• Business Intelligence: Expertise in BI tools such as Qlik, Tableau, Power BI, Looker, Qlik, or similar.
• Ability to design and develop interactive dashboards and reports that drive business insights.
• Experience with lake house technologies such as Microsoft Fabric, Synapse, Databricks, Delta Lake, Apache Hudi, or Apache Iceberg.
• Knowledge of how to leverage lake house architectures for scalable and efficient data processing and analytics.
• Programming Languages: Proficiency in programming/scripting languages such as SQL, Python, or R.
• Analytical Thinking: Strong analytical skills with the ability to design and implement complex data solutions.
• Problem-Solving: Excellent problem-solving skills with a proactive approach to resolving data issues.
• Communication: Effective communication skills, with the ability to present technical concepts to non-technical stakeholders.
• Leadership: Proven leadership abilities with experience in managing cross-functional teams and projects.
• Project Management: Strong organizational skills with experience in managing and delivering data projects on time and within budget.

Minimum Education: BS or equivalent experience

Minimum Experience: 5 years Preferred Experience: 10+ years