The Architect, Business Analytics and Data Intelligence designs scalable data pipelines and data models. Establishes guidelines for development standards and best practices for data pipeline build. Ensures data security and data quality is embedded in the data platform implementation framework. Provide cross functional support for data architecture and enterprise data management.
Responsibilities- Manage technology architecture, standards, and design patterns ensuring alignment between business goals and technology strategy, managing collaboration with business leaders to analyze and capture business needs.
- Analyze solution designs, blueprints, and architecture decision records.
- Develop evaluation of technology alternatives for strategy and solution proposals, including build vs. buy analysis.
- Deliver architecture governance and compliance with enterprise standards and frameworks.
- Recommend improvements to technical roadmaps aligned with business strategy, coordinating with department leaders.
- Manage technical debt assessment, modernization strategies, and migration planning.
- Ensures compliance with all policies and standards, as well as state, federal and other regulatory bodies.
- This is not intended to be a comprehensive list of the duties and responsibilities of the position and the duties and responsibilities may change.
Qualifications- Bachelor's Degree in Arts/Sciences (BA/BS) Computer Science, Data Science, Information Systems, or related field
- 10+ years experience in data engineering
- Expertise in the Modern Data Platform stack (Snowflake, Databricks).
- Expertise with any major cloud platforms and services (AWS, GCP, Azure)
- Experience with data ingestion and orchestration tools and frameworks, such as dbt, dagster, airflow, matillion,
- Strong proficiency in SQL, Python, and data modeling techniques.
- Strong knowledge of data extraction patterns and best practices.
- Solid understanding of dimensional modeling and its application in analytics.
- Strong problem-solving skills with a focus on delivering scalable and efficient solutions.
- Working knowledge in the implementation of AI in data engineering lifecycle
- Excellent communication and collaboration skills, with experience in client-facing roles.
Knowledge/Skills/Abilities- Collaborate with stakeholders to design and implement scalable data engineering solutions.
- Design of data pipelines, ensuring efficient extraction, transformation, and loading (ETL) processes for structured and unstructured data
- Apply best practices in dimensional modeling to create robust and scalable data models for analytics and reporting.
- Leverage tools such as Python, SQL, Snowflake native features to develop advanced data transformation and integration processes.
- Optimize data storage and retrieval mechanisms to support high-performance analytics workloads.
- Implement and manage hybrid analytics workloads using AWS Cloud infrastructure, including networking and security configurations.
- Collaborate with analytics and BI teams to ensure seamless integration of data assets into Power BI and other reporting platforms.
- Stay informed about emerging trends and technologies in data engineering and cloud analytics to enhance solution delivery.
- Familiarity with advanced analytics tools and concepts, including machine learning workflows.
- Knowledge of data visualization tools such as Power BI.
- Experience with Agile methodologies for project management.
Benefits- Medical, dental, and vision insurance
- Paid time off
- Tuition Reimbursement
- 401K
- Paid time to volunteer in your local community
Compensation Information
$150,000.00-$194,000.00 / Annually
