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Senior Data Solutions Architect
1 month ago
- In collaboration with the Architecture Team and Principal Engineers, create and maintain a set of data architecture principles and ensure their adoption across data-related teams.
- Support Product Management Team in driving the execution of a comprehensive data strategy that aligns with corporate vision and business objectives.
- Establish and enforce robust data governance policies, processes, and standards to ensure data quality, integrity, security, and compliance with regulatory requirements.
- Define and promote best practices in data management, ensuring consistency and reliability across the organization, in line with the broader enterprise architecture principles.
- Develop and maintain technology data architecture roadmap and drive execution of the roadmap.
- Work closely with operations, data science, and engineering teams to understand data needs and translate them into detailed initiatives and products.
- Evaluate and identify new data technologies for implementation, coordinating with the Lead Enterprise Architect to ensure they fit within the overall enterprise architecture.
- Deliver quality architecture artifacts on schedule and within cost.
- Do requirements analysis, system/software design and analysis, development/software metric creation and analysis, system risk analysis, integration, and test metrics.
- Provide leadership to the software delivery teams and enforce standard company policies and procedures that adhere to software development standards and architecture principles
- Bachelor’s degree in computer science or related field; Master’s degree is highly preferred.
- 3+ years of recent experience in Data Architecture, Data management, data integration, and data warehousing.
- 3+ years of recent experience designing, developing, and delivering enterprise data solutions.
- Proven experience in data architecture and engineering, including designing, implementing, and managing complex data systems.
- Proficiency with database management systems, both SQL (e.g., SQL Server, PostgreSQL) and NoSQL (e.g., MongoDB, Cassandra).
- Experience influencing agile software delivery teams
- Strong collaboration skills to work effectively with cross-functional teams, including operations, data science, and engineering peers.
- Experience developing and implementing cloud-based data architectures; direct experience with data management products in Azure and Google cloud required (for example, Azure HDInsight, GCP Dataproc, Azure Synapse, Google BigQuery, Service Bus, Pub/Sub).
- Experience with data-driven design principles.
- Experience in processing streaming and batch data at both scale and velocity.
- Strong skills in data modeling and design, including experience with tools like Erwin, Lucidchart, or similar.
- Proficiency in programming languages commonly used in data engineering and data science (e.g., Python, R, Java, Scala).
- Experience with data visualization tools (e.g., Tableau, Power BI) to create insightful and actionable data presentations.
- Understanding of machine learning and AI concepts, and experience integrating these capabilities into data solutions at scale.
- Proficient in evaluating and conveying the trade-offs involved in various technological designs.
- Leading efforts to resolve critical issues.