Data Engineer

SOM•Chicago, IL

17d•$160,000 - $180,000

About The Position

At SOM, we are a collective committed to shaping a better future for our clients, communities and planet. We aspire to create the most sustainable, impactful work through creative, interdisciplinary teams with all the resources and diversity of a global firm. We value those who are passionate about excellence, innovation, integrity, inclusivity, and collaboration. Together we can achieve great things. Success at SOM Means Ideas: We believe in a meritocracy of ideas. We look to everyone to actively contribute to the discourse in the firm. Knowledge: We believe that expertise is the result of lifelong learning. We are not expected to know everything, but rather to passionately pursue answers, develop new skills and deepen our knowledge. Product: We strive for excellence in the concept, quality, and delivery of our work. Individual: We value individuals who bring the highest standards of professionalism and personal integrity in the way they work. Each person can develop and contribute their wealth of attributes, skills and knowledge to support the overall health of the firm. Team: We value the power of interdisciplinary integration. A positive team culture in which everyone collaborates openly towards common goals is essential. Firm: We have a history of making transformative contributions to the profession and our communities. We are constantly innovating and attempting to bring new approaches, solutions and processes to our work.

Requirements

Seven or more years of experience in a data engineering, cloud data, or DevSecOps-focused role.
Hands-on experience with cloud data platforms (Databricks or Snowflake & AWS) and IAM design for data access.
Proficient in infrastructure-as-code and scripting tools: Terraform, Git, Python, and SQL.
Familiarity with enterprise systems such as Salesforce, Workday, Nasuni/Panzura, and the Google Workspace or Microsoft Office suites.
Comfortable administering and analyzing data systems across Windows, macOS, and Linux environments.
Skilled in technical documentation and standard operating procedure development for complex data workflows.
Clear and direct communicator, able to collaborate across technical and non-technical design teams.
Demonstrated knowledge of Architecture, Engineering, and Construction Industry data formats (Revit, Rhino, etc.), data modeling, and common pipeline bottlenecks.

Responsibilities

Investigates and responds to data pipeline incidents, including ingestion failures, data quality alerts, and schema drift issues.
Assesses and remediates data misconfigurations and unauthorized access across cloud data services and storage platforms.
Deploys, manages, and maintains data-specific infrastructure such as Snowflake warehouses, Databricks clusters, and logging pipelines.
Designs and maintains automation scripts and infrastructure-as-code to support data operations (e.g., Terraform, Git, Python, SQL, Lambda).
Translates written data governance policies and standards into technical controls; ensures enforcement and flags any violations or exceptions.
Implements and audits IAM controls across cloud platforms (AWS), SaaS tools (Salesforce, Workday), and enterprise data systems.
Maintains secure API integrations and data encryption practices for movement between AEC design tools and the Data Lakehouse.
Monitors alerting systems, tunes false positives in data quality checks, and investigates anomalous data behavior using logs.
Maintains operational and procedural documentation, including data lineage diagrams, runbooks, and ETL tool configurations.
Supports post-incident activities, including root cause review of data loss or corruption and implementation of corrective actions.
Coordinates with infrastructure and engineering teams to ensure secure configuration standards are applied across data services.
Assists in collecting audit and compliance evidence related to data privacy and security controls.
Contributes to team knowledge sharing and helps mentor junior staff on modern data engineering practices.
Keeps current with data threats, engineering frameworks (Lakehouse), and tool capabilities.
Collaborates with leadership to support strategic AI initiatives and continuous improvement projects.
Contributes to defining the technical scope of projects and identifying risks in data system design or operations.
Promotes a "data-first" mindset among peers and across technical teams.
Inspires and leads others by example, participates in staff mentoring and training, clearly defines team member expectations and responsibilities, empowers others, and delegates where appropriate based on team members’ recognized abilities and potential.
Directly supervises staff and is committed to direct reports’ professional development.
Develops and engages in talent strategy to find specialists, leaders, and future professionals for the firm through resume review and interviews.
In collaboration with team members, develops a clear and consistent work plan to achieve the project budget, deliverables, and schedule.
Actively engages in internal and external professional development opportunities.
Contributes to the implementation of sustainable strategies in all project assignments and the associated development of staff knowledge.
Contributes to the development of standards, policies, and procedures.
Protects SOM from financial and legal risk.

Benefits

Health and Wellness: Medical, dental, vision, disability, and life & accident insurance
Savings: 401K matching, pre-tax spending accounts, and employee discount programs
Work/Life Balance: Inquire about our approach to flexible schedules, paid family leave, paid vacation, backup child and elder care, and an employee assistance program
Professional Development: Reimbursement for professional licenses, associated renewals, and exam fees as well as specialized in-house career development

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