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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Skidmore, Owings & Merrill - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $160,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Microsoft Windows, Amazon Web Services, Data Analysis, Apple Mac Systems, Autodesk Revit, Software as a Service, Cloud Database, Data as a Services, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Loss, Data Security, Data Systems, Identity and Access Management, Python (Programming Language), Linux System Administration, Microsoft Office, Cloud Services, DataOps, Salesforce.Com, SQL Databases, Data Logging, Scripting, Enterprise Software Applications, Snowflake, Git, Rhino, Data Lineage, Gsuite, Data Lakehouse, Functional Programming, Terraform, Data Pipelines, Devsecops, Workday, Databricks - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=f30cc04c7a5b1640 ## About the Role * 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. ## Description * 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. Position 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. Leadership Responsibilities * 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. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Stop Committing Your Secrets - GIt Hooks To The Rescue!](https://www.wearedevelopers.com/videos/573-stop-committing-your-secrets-git-hooks-to-the-rescue) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)