Senior Data Engineer

Alined Consulting Group • Full-time • Niles, IL, US • $135k - $147k / year • 2d ago

You'll also be collaborating pretty closely with project teams, IT leadership, and business stakeholders — so it's not just a heads-down technical role. You'd be part of the planning conversations, helping define scope, timelines, and making sure the solutions are aligned with what the business needs

Key Responsibilities:

Design and implement scalable data infrastructure, including databases, data warehouses, and data lakes.
Develop and maintain ETL/ELT processes to ingest, transform, and load data from various sources.
Create and manage CI/CD pipelines to automate deployment of data solutions.
Ensure data accuracy, consistency, and reliability through rigorous quality monitoring.
Perform data modeling and design for reporting and analytics platforms.
Collaborate with business users to design and support Business Intelligence (BI) reports.
Conduct proof of concepts and support the adoption of modern data engineering tools (e.g., Azure Data Factory, Databricks, Microsoft Fabric).
Document system configurations, technical specifications, and support procedures.
Translate business requirements into technical data solutions.
Maintain clear communication with stakeholders and provide regular project updates.
Support and implement data governance, security, and compliance frameworks.

Required Qualifications:

Bachelor's degree in Computer Science, Management Information Systems, or related field.
Minimum of 7 years of experience in full solution development lifecycle, including data processing and reporting applications.
Hands-on experience with:
Data architecture and ecosystem design (e.g., ODS, data lakes, data warehouses)
ETL/ELT tools (e.g., SSIS, Informatica, DataStage)
BI tools (e.g., Power BI, Tableau, Domo, Infor Birst)
Data modeling tools (e.g., ER/Studio, Erwin)
SQL Server tuning and database design
Working with non-relational data sources (flat files, Excel, JSON, APIs)

Preferred Qualifications:

Experience with cloud platforms (e.g., Microsoft Azure, AWS, Google Cloud).
Exposure to AI/ML technologies and concepts.
Experience with data quality and master data management tools (e.g., Talend, Informatica).