Data Engineer

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