Summary

The Data Architect Lead is responsible for designing, implementing, and managing scalable data architectures that support enterprise analytics and business intelligence.  Work closely with business leadership to align data strategy with organizational goals while managing a small team of ETL and BI developers. 

Primary Duties

Design and implement scalable, high-performance data architectures leveraging Databricks, Delta Lake, and Lakehouse best practices. Ensure that the organization's data practices follow legal requirements related to data privacy and protection, such as GDPR, CCPA, HIPPA and other data regulations. Lead data ingestion, transformation, and modeling pipelines with Databricks and cloud-based data pipelines Optimize Databricks clusters, data workloads, and query performance for cost efficiency and speed. Implement role-based access control (RBAC) and attribute-based access control (ABAC) Act as the key liaison between business stakeholders and technical teams, translating business needs into technical solutions. Partner with senior leadership to drive enterprise data strategies. Present architectural recommendations, roadmaps, and technology adoption plans to senior leadership. Lead and mentor a small team of ETL and BI developers, providing technical guidance and career development support. Oversee the end-to-end development of data pipelines, reporting solutions, and analytics platforms. Foster a culture of innovation, collaboration, and best practices within the team.

Working Relationships

The Data Architect Lead reports to the VP of IT. 

Compensation

The initial annual compensation for this position will range from $140,000 - $161,000 based on skills and experience.

Job Qualifications:

Education: Bachelor’s degree in Computer Science, Information Systems or related field from an accredited college or university recognized by the United States Department of Education or equivalent. Preferred Education: Master’s degree in Computer Science or Information Systems from an accredited college or university recognized by the United States Department of Education or equivalent. Years of Experience: Seven years of experience in data architecture, data engineering, and analytics. Experience in modern data warehousing, data lakes, and real time data processing. Preferred Experience: Experience implementing machine learning pipelines and AI-driven analytics. Experience designing architectures for real-time and batch processing of loT data from sensors, edge devices, and connected systems using Databricks, Delta Live Tables, and Kafka. Experience in managing and processing unstructured data (text, images, videos, IoT sensor data) using cloud-native solutions and AI-driven analytics. Licenses/Certification: Software/Equipment Knowledge: Databricks (including Delta Lake, Unity Catalog, MLflow and Databricks SQL) SQL, Python, and ETL/ELT pipelines BI tools (e.g., Power BI, Tableau) Azure cloud platform and cloud-native data services. Deep knowledge of data modeling, ETL frameworks, and Lakehouse architecture Knowledge of data security, privacy, and compliance frameworks GDPR, CCPA, HIPAA, etc. (Preferred) Other Considerations: Excellent communication and stakeholder management skills with the ability to present technical solutions to non-technical audiences. Strong Leadership and team management skills with experience mentoring developers.

Physical Requirements and Working Conditions

Normal works hours are 8:00a.m. to 5:00p.m. Monday through Friday. Additional time may be required during heavy workloads or to meet deadlines.

Physical Requirements: Ability to sit for long periods of time, ability to communicate verbally, and in writing, and ability to handle long periods of screen time.

Fit for Duty

All employees will participate in the Fitness for Duty Program. This program includes a post-offer physical examination and drug screening and post-employment random drug screening. There are extensive smoking restrictions in and around the facility.

NAES Safe

Safety is a core value of NAES and as a condition of employment, all employees are expected to be mentally alert and work safely at all times.  Additionally, employees are required to adhere to all safety warnings and posted safety signs whenever on company property.  Furthermore, employees must follow all NAES safety rules and procedures.  Effectiveness in carrying out this responsibility is part of the evaluation of each employee’s performance.

NAES is committed to a diverse and inclusive workplace. It is the practice of NAES to seek employees of the highest quality and to select individuals on the basis of merit and competence, without regard to race, color, religion, national origin, gender, gender identity, sexual orientation, age, disability, military status or affiliation protected under USERRA, or any other basis of discrimination prohibited by applicable local, state and federal law.