Data Architect / Data Engineering Lead
HireWell
Libertyville, IL, United States
5 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Compensation
$140,000.0 - $170,000.0
Working hours
Regular working hours
Job source
Tech stack
Sql Data Warehouse
Application Programming Interfaces (APIs)
Microsoft Azure
Information Systems
Databases
Continuous Integration
Information Engineering
Data Governance
Data Integration
Extract Transform Load (ETL)
JSON
Python (Programming Language)
+9 more
Transact-SQL
Azure Data Factory
Sql Optimization
Snowflake
Git
Information Technology
Data Management
Restful APIs
Data Pipelines
Job description
- Design and maintain the enterprise data architecture, including how data moves between operational systems, the cloud data warehouse, and downstream consumers
- Design conceptual, logical, and physical data models, including dimensional models that support reporting and analytics
- Build, maintain, and monitor ETL/ELT pipelines that bring data from relational databases, NoSQL document stores, and cloud SaaS applications into the warehouse
- Identify and resolve database and pipeline performance issues, including query tuning, indexing, warehouse sizing, and cost optimization
- Establish data quality checks, monitoring, and alerting so data is accurate, complete, and timely
- Define and enforce data standards and naming conventions, and maintain a data dictionary and data lineage
- Implement data security and access controls, including role-based access, data masking, and protection of sensitive and regulated data
- Partner with the reporting team to deliver curated, certified datasets for self-service dashboards
- Partner with data science to provide clean, well-structured data for analysis and modeling
- Work with business analysts, architects, and developers to define data requirements for new projects and system changes
- Evaluate and recommend data tools, platforms, and integration approaches
- Cover some database administration work, since there is no dedicated DBA on the team
- Resolve support cases related to data, integrations, and pipelines
Requirements
- 7+ years of experience in data engineering, database development, or data architecture
- Proven experience designing data models, including dimensional, relational, and NoSQL document models
- Hands-on experience with Snowflake, including data loading, modeling, performance tuning, and cost management
- Strong experience with MS SQL Server development and administration
- Experience with NoSQL document databases such as Azure Cosmos DB or similar
- Demonstrated experience building and supporting production ETL/ELT pipelines
- Experience integrating data from cloud SaaS applications through APIs and connectors
- A strong ability to diagnose and resolve performance issues across databases and pipelines
- Advanced SQL and T-SQL
- Experience with ELT/ETL tools such as Fivetran, Matillion, Azure Data Factory, or Airbyte
- dbt and Python, plus working knowledge of REST APIs and JSON
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent experience
- A collaborative approach, comfortable both designing new systems and improving existing ones, and able to prioritize multiple projects in a fast-paced environment
Nice to Have
- Snowflake SnowPro or a Microsoft Azure data certification
- Experience leading a migration from legacy reporting databases to a cloud data warehouse
- Experience with data governance frameworks and master data management
- Git and CI/CD for data pipelines
- Exposure to supply chain, logistics, or regulated-industry data
About the company
Hirewell is partnering with a growing, established distribution company in the northern Chicago suburbs to hire a Data Architect / Data Engineering Lead. This is the dedicated owner of the company’s data foundation. Roughly one third of the role is architecture and two thirds is hands-on engineering, so you’ll design the models and build the pipelines. You’ll deliver trusted, well-modeled data that powers reporting, self-service analytics, and data science. The company builds much of its technology in-house, which gives you real influence over tools, standards, and approach.
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