Data Engineer I

Duly Health and Care; Downers Grove (IL); On-site; USD 65,000 - 85,000; Full time

Benefits offered by this job

Medical, dental, and vision benefits

Tuition reimbursement

Immediate 401(k) match

Parental leave (up to 12 weeks)

Job summary

Duly Health and Care is seeking an early-career Data Engineer I to join the Data & Analytics team in Downers Grove, IL. This onsite role focuses on building, operating, and improving data pipelines that support analytics, reporting, and AI across the enterprise, using a cloud data platform for ingestion, transformation, orchestration, and monitoring.

You will collaborate with architects, analysts, BI developers, and data scientists to turn source data from systems, databases, APIs, and files

Qualifications

• Bachelor’s degree in CS/IS/related field or 2 years of related experience.
• 0-2 years in relational databases, data engineering, or software development (internships count).
• Proficiency in SQL for data analysis and transformation.
• Experience with Python or other scripting languages is beneficial.
• Experience with Databricks, Spark, Delta Lake, Azure Data Factory or other cloud platforms (Azure preferred).
• Experience with Git and CI/CD practices is beneficial.

Responsibilities

• Build, test, and maintain batch and incremental data pipelines into the enterprise lakehouse.
• Create data transformations using SQL and Python (bronze/silver/gold layers).
• Support orchestration and scheduling of pipelines using data platform tools.
• Apply version control, code review, and testing practices to pipeline code.
• Optimize SQL queries and pipeline performance for reliability and cost.
• Monitor runs, troubleshoot data issues, and resolve failures.

Skills

SQL

Python

Databricks

Spark

Delta Lake

Azure Data Factory

Azure

Git

CI/CD

ETL/ELT

Education

Bachelor’s degree or 2 years related experience

Job description

Duly Health and Care is seeking an early-career Data Engineer I to join the Data & Analytics team. This onsite role in Downers Grove, IL focuses on building, operating, and improving data pipelines that support analytics, reporting, and AI across the enterprise, using a cloud data platform for ingestion, transformation, orchestration, and monitoring.

The position plays a key part in turning source data from systems, databases, APIs, and files into reliable, well-structured datasets within an enterprise lakehouse. You will collaborate with architects, analysts, BI developers, and data scientists to understand data needs and deliver trustworthy outputs.

What you’ll be doing

• Build, test, and maintain batch and incremental data pipelines that move data into the enterprise lakehouse
• Create data transformations using SQL and Python, including movement through layered structures (for example, bronze/silver/gold)
• Support orchestration and scheduling of pipelines using the organization’s data platform tools
• Apply version control, code review, and testing practices to pipeline code
• Optimize SQL queries and pipeline performance to improve reliability, reusability, and cost
• Monitor pipeline runs, troubleshoot failures, and assist with timely resolution of data issues
• Implement data quality rules, validation checks, and alerting within pipelines
• Follow organizational standards for data privacy and protection of PHI/PII, including support for access control and security practices
• Assist in assessing how source system changes impact downstream pipelines, models, and reports
• Document pipelines, data flows, runbooks, and release notes as required by the project delivery methodology
• Partner with business stakeholders to understand data definitions and requirements
• Learn from senior engineers through code reviews, design reviews, and mentoring
• Identify opportunities to improve data engineering standards, automation, and documentation
• Perform additional duties as assigned

Qualifications

• Bachelor’s degree in computer science, information systems, data science, engineering, or related field; or 2 years of related experience; or equivalent education and experience
• 0-2 years of experience with relational databases, data engineering, or software development (internships, co-ops, and academic projects count)
• Proficiency in SQL for data analysis and transformation
• Experience with Python or another scripting language is beneficial
• Experience with Databricks, Spark, Delta Lake, Azure Data Factory, or other cloud data platforms (with Azure preferred) is beneficial
• Experience with Git and CI/CD practices is beneficial
• Healthcare or Epic Clarity experience is not required; training provided
• Understanding of relational database concepts, data modeling, and ETL/ELT patterns
• Strong SQL skills including joins, CTEs, and window functions
• Strong analytical, organizational, and problem-solving skills
• Strong written and verbal communication skills, including explaining technical work to non-technical audiences
• Detail-oriented with a commitment to documentation and testing
• Ability to work independently and in a team environment
• Curiosity and desire to learn modern data engineering practices
• Familiarity with data governance, data security, or privacy concepts is helpful

Skills and tools

• SQL, Python, Databricks, Spark, Delta Lake, Azure Data Factory, Azure, Git, CI/CD

Compensation and benefits

• Base pay range: $65,000 - $85,000 per year
• Comprehensive medical, dental, and vision benefits including healthcare navigation assistance
• Mental health benefit at no cost
• Employer provided life and disability insurance
• $5,250 Tuition Reimbursement per year
• Immediate 401(k) match
• 40 hours paid volunteer time off
• Culture committed to community engagement and social impact
• Up to 12 weeks parental leave at 100% pay, plus a financial benefit for adoption and surrogacy for non-physician team members once eligibility requirements are met
• Additional compensation may be available through shift differentials, bonuses, and other incentives

Artificial Intelligence Disclosure: AI tools may be used in some portions of the candidate review process for this position; however, all employment decisions will be made by a person.