Data Engineer
Legence· enterprise· Construction· Oct 16, 2026 · 12d agoReposted 11 days ago
Minneapolis, MN, USA
In office
Full-time
Mid
$100K–$160K est.
3+ years exp
Before you apply
Ghost Signal:
Re-promoted recently, but this role has been open since June 17, 2026 — 132 days, never closed.
Job description
Data Engineer
Position Overview
We are seeking a highly skilled Data Engineer to design, develop, and maintain scalable data solutions that support analytics, reporting, and business operations across the organization. This hands-on role requires expertise in data architecture, data integration, cloud platforms, and modern data engineering practices.
The ideal candidate will be responsible for building robust data pipelines, optimizing data platforms, and ensuring the availability, quality, and reliability of enterprise data. This role will interact directly with business stakeholders and end users to gather requirements, support testing efforts, and deliver scalable solutions.
This position is remote, with preference given to candidates located near a Legence office location.
Key Responsibilities
Data Engineering & Architecture
Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, Python, SQL, and related technologies.
Develop and optimize enterprise data models utilizing dimensional modeling techniques, including star and snowflake schemas.
Implement and manage data warehouses, data lakes, and lakehouse architectures.
Integrate data from ERP systems, APIs, cloud platforms, databases, and third-party applications.
Build scalable frameworks for data validation, monitoring, and quality assurance.
Establish and maintain data governance standards, documentation, and lineage.
Cloud Data Platform Development
Configure and support cloud-based data platforms and environments.
Develop, optimize, and maintain complex SQL queries, stored procedures, and data transformations.
Improve performance and reliability of data pipelines through optimization and monitoring.
Implement security controls and access management to protect enterprise data.
Automate data processing workflows and scheduled jobs.
Stakeholder Collaboration
Partner with business stakeholders to understand data requirements and translate them into technical solutions.
Support solution testing, deployment, and ongoing maintenance activities.
Provide technical guidance and recommendations regarding data architecture and platform design.
Document technical designs, data flows, and operational procedures.
Required Qualifications
Technical Skills
3+ years of hands-on Data Engineering experience.
Strong SQL skills, including database design, performance tuning, and query optimization.
Experience building and maintaining ETL/ELT pipelines.
Experience with Azure Data Factory, Microsoft Fabric, Azure Synapse Analytics, Azure SQL Database, or similar cloud-based data platforms.
Proficiency with Python for data transformation, automation, or integration tasks.
Solid understanding of data warehousing concepts, dimensional modeling, and data architecture best practices.
Experience integrating data from APIs, enterprise applications, and cloud services.
Data & Analytical Expertise
Strong understanding of data modeling techniques and relational database concepts.
Experience performing data profiling, validation, and quality assessments.
Ability to translate business requirements into scalable technical solutions.
Understanding of data governance, metadata management, and data lineage principles.
Professional Competencies
Strong problem-solving skills and a hands-on, solution-oriented mindset.
Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.
Detail-oriented with a commitment to code quality, testing, and documentation.
Demonstrated ability to leverage automation and AI-enabled tools to improve development efficiency.
Preferred Qualifications
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
Microsoft DP-203 (Azure Data Engineer Associate) certification or equivalent.
Experience with Databricks, Spark, or PySpark.
Familiarity with Git, Azure DevOps, and CI/CD pipelines.
Experience working with ERP, operational, financial, or construction-related datasets.
Experience developing data lake or lakehouse architectures.
Knowledge of data science concepts, machine learning workflows, or predictive analytics.
Technical Environment
Microsoft Fabric
Azure Data Factory
Azure Synapse Analytics
Azure SQL Database
Azure Data Lake Storage
SQL Server
Python
Databricks (preferred)
Git / Azure DevOps
APIs and Cloud Integration Services
What Makes You Stand Out
Experience designing and implementing enterprise-scale data platforms.
Proven success building and optimizing complex ETL/ELT processes.
Experience modernizing legacy data environments and improving data quality.
Strong understanding of cloud-native data architectures and governance practices.
Experience mentoring team members and promoting data engineering best practices.
Contributions to technical communities, open-source projects, blogs, or speaking engagements.
This is a hands-on technical role requiring daily interaction with data, code, integrations, and cloud-based data platforms. The ideal candidate thrives in environments where they can build scalable solutions from the ground up and take ownership of the full data lifecycle.
Base salary: $105,000-$120,000 per year. This role is also eligible for an annual performance‑based bonus. Bonus eligibility and payout are determined by role, individual performance, and company performance, and are not guaranteed.
Unable to provide sponsorship for this position.
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Keywords to mirror
azurepythonsqlaici/cdmachine learning
- Platform
- dayforce
- Effort
- medium