Data Engineer

Contruent; Naperville (IL); On-site; USD 90,000 - 120,000; Full time

Job summary

A technology services company is seeking a Data Engineer to enhance its analytics infrastructure and reporting capabilities. The ideal candidate will have strong SQL skills and experience with AWS services, and will be responsible for maintaining data system performance, developing ETL pipelines, and optimizing Power BI dashboards. This is a full-time position at the mid-senior level in Naperville, Illinois.

Qualifications

• 3–5 years of experience as a Data Engineer, Data Scientist, or Database Developer.
• Advanced proficiency in SQL and database administration.
• Hands-on experience building ETL pipelines with AWS Glue or equivalent tools.
• Strong experience with Power BI for data modeling and performance tuning.

Responsibilities

• Maintain and optimize large SQL Server and AWS RDS databases.
• Design, build, and manage ETL pipelines and data integrations.
• Develop and enhance Power BI datasets and dashboards.
• Partner with business stakeholders to translate requirements into data models.

Skills

SQL engineering

ETL processes

Data modeling

Power BI

AWS services

Python

Tools

AWS Glue

SQL Server

AWS RDS

Git

Job description

Join to apply for the Data Engineer role at Contruent

We are seeking a Data Engineer to help advance our analytics infrastructure, data pipelines, and reporting capabilities. This role will work closely with the Manager of Data Science & AI Engineering to manage and optimize our SQL environments, develop automated data flows, and modernize our Power BI ecosystem.

You'll be responsible for maintaining the integrity and performance of our data systems, enabling scalable and reliable analytics across the organization. The ideal candidate combines strong SQL engineering skills with a deep understanding of data modeling, ETL, and business intelligence.

Key Responsibilities

• Maintain and optimize large SQL Server and AWS RDS databases, ensuring performance, reliability, and scalability.
• Design, build, and manage ETL pipelines and data integrations using AWS Glue, Lambda, and related AWS services.
• Develop and enhance Power BI datasets, models, and dashboards with an emphasis on usability, governance, and performance.
• Partner with business stakeholders to translate requirements into well‑designed data models and reporting solutions.
• Implement best practices for database indexing, query optimization, and data lifecycle management.
• Support the deployment of data‑driven and AI‑enabled applications alongside the Data Science & AI Engineering team.
• Contribute to data quality monitoring, metadata management, and documentation of data sources and transformations.
• Assist in modernizing legacy reporting workflows and migrating data assets to AWS cloud platforms.

Required Skills & Experience

• 3–5 years of experience as a Data Engineer, Data Scientist, or Database Developer.
• Advanced proficiency in SQL and database administration (SQL Server, AWS RDS).
• Hands‑on experience building ETL pipelines with AWS Glue, Lambda, or equivalent tools.
• Strong experience with Power BI (data modeling, DAX, Power Query, and performance tuning).
• Familiarity with Python for scripting and automation.
• Understanding of modern data architectures (star/snowflake schemas, data lakes, and cloud‑native data design).
• Solid grasp of version control (Git) and CI/CD principles for data deployments.
• Ability to collaborate across technical and business teams to deliver reliable, scalable analytics.
• Experience handling sensitive data through isolation and anonymization.

Preferred Qualifications

• Experience with AWS analytics stack (S3, Glue Data Catalog, Athena, Redshift, or Bedrock).
• Exposure to data orchestration tools (Airflow, Step Functions, or Databricks Workflows).
• Familiarity with API‑based integrations and data ingestion from SaaS systems (e.g., HubSpot, Unanet, or Salesforce).
• Strong understanding of data governance, security, and change management within analytics environments.
• Interest in or exposure to machine learning, AI automation, or predictive analytics workflows.

Tech Stack You're Will Work With

• Databases: AWS RDS, SQL Server
• Cloud: AWS (Glue, S3, Lambda, Bedrock, SageMaker)
• Languages: SQL, Python
• Analytics: Power BI, AWS QuickSight
• ETL / Pipelines: AWS Glue, Python scripts, SQL stored procedures

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Information Technology

Industries

Software Development

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