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The Data Architect supports a world-class analytics experience by implementing recognized industry best practices, including state-of-the art data control and transformation practices to enable self-service analytics throughout the organization. An in-depth understanding of OLTP and OLAP is essential for success in this position.
Responsibilities:
The Data Architect supports a world-class analytics experience by implementing recognized industry best practices, including state-of-the art data control and transformation practices to enable self-service analytics throughout the organization. An in-depth understanding of OLTP and OLAP is essential for success in this position.
The Data Architect responsibilities include:
- Planning and supporting the design and implementation of data centric infrastructure to support the analytics environment.
- Maintaining an in-depth knowledge of the organization’s data solutions and leveraging that knowledge to continuously evolve data structure for analytics at the organization.
- Architect data structures for reports and dashboards supporting internal teams and overall self-service infrastructure.
- Assisting the teams, product owners, and organization with implementing data modeling best practices.
- Participating in team collaboration through idea-sharing and brainstorming sessions.
- Provide direction on data migration, data lineage, master data management, and overall data strategy.
- Coordinating with other departments within the organization to effectively understand where additional data resources can be curated to enhance overall analytics strategy.
- Assisting the leadership team to set direction and identify solutions addressing opportunities and challenges.
- Providing ongoing feedback and assessment of project status and issues to the director.
- Demonstrating a hands-on, high energy work ethic and championing a team player attitude.
- Continually evaluate data analytics industry trends and new technologies.
- Prioritizing, coordinating, and managing varying priorities in a fast-paced environment.
Experience
- Bachelor's or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
- 3+ years of experience in a data engineering role or equivalent.
- Proficiency with programming languages such as Python, SQL, or Scala.
- Experience with big data tools such as Hadoop, Spark, or Kafka.
- Expertise in designing and optimizing ETL processes.
- Strong knowledge of data modeling, data warehousing, and working with relational databases (e.g., PostgreSQL, MySQL, Oracle).
- Experience with cloud platforms such as AWS, Google Cloud, or Azure.
- Familiarity with APIs, data lakes, and large-scale data architectures.
- Ability to collaborate in cross-functional teams and communicate technical concepts effectively.
- Strong problem-solving skills with attention to detail and ability to handle large datasets.
Preferred:
- Experience with real-time data processing frameworks (e.g., Apache Flink, Storm).
- Familiarity with machine learning pipelines and integrating them into data workflows.
- Knowledge of DevOps practices and tools (e.g., Docker, Kubernetes, Jenkins).
- Previous experience working in Data Science or Business Intelligence teams.
Preferred
- Familiarity with Jira, Jira Service Desk, cloud architecture.
- Experience with SOAP and REST API’s
- Experience with Python or R
- Microsoft Certifications
- Advertising or marketing knowledge a plus
- Experience with data architecture, data modeling, database design and the use of data warehouses and data marts.
- Experience with star and snowflake database design and modeling.
- Experience with Alteryx Server and Self-Service environments
- Experience working in an agile development environment
Requirements
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