Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Work setup in the employer’s posting: On-siteFrom the employer’s posting
Design and maintain data pipelines using Azure Data Factory, Synapse, and Databricks
Implement and support Microsoft Fabric lakehouses, warehouses, and dataflows
Build and maintain curated datasets and semantic models for Power BI
Automate scheduling and error handling so recurring data loads run reliably
Implement data quality rules, validation, and monitoring
Design, build, and maintain scalable data pipelines and data integration workflows using Microsoft Azure services
Implement and support Microsoft Fabric solutions, including dataflows, lakehouses, data warehouses, and real-time analytics features
Develop and maintain curated datasets and semantic models that support Power BI reporting and self-service analysis
Implement scheduling, orchestration, automation, and error handling so recurring data loads run reliably with minimal manual intervention
Implement data quality rules, validation, and monitoring so issues are caught before they reach reporting or decision-making
Communication and Working Style
Required Education and Experience · Bachelor's degree in computer science, Data Engineering, Information Systems, or a related field preferred (or equivalent experience). · At least 3 years of experience as a Data Engineer, ideally in professional services or large enterprise environments. · Demonstrable expertise in building data pipelines and cloud data solutions on Azure. · Experience with Microsoft Fabric is strongly preferred. Technical Skills
· Apply dimensional modeling and other established modeling patterns so data is understandable, reusable, and consistent across reporting. · Write and tune advanced SQL, along with Python or PySpark notebooks, for complex transformation work. · Monitor, troubleshoot, and improve data workflows, resolving failures and performance bottlenecks at the source rather than working around them.
Technical Skills · Strong hands-on experience with Microsoft Azure data services (e.g. Data Factory, Synapse Analytics, Data Lake, Databricks).· Direct experience delivering solutions using Microsoft Fabric.· Advanced SQL skills and experience with data modeling, transformation, and integration.· Knowledge of Python or other scripting languages is an advantage.· Familiarity with data governance, data quality, and compliance frameworks.· Certification in Microsoft Azure data engineering or Microsoft Fabric is a plus. Communication and Working Style
Position Overview NAC is looking for an experienced Data Engineer to join our delivery team, with a specific focus on designing, building, and optimizing data solutions on Microsoft Azure and Microsoft Fabric. This role is critical to helping NAC unlock the full value of our data assets, supporting advanced analytics, reporting, and digital transformation across the firm. The ideal candidate is confident working with a modern data stack, automating data pipelines, and delivering reliable, scalable, high-quality data solutions in enterprise environments. The day-to-day work ranges from ingesting data out of firm business systems into a governed lakehouse to tuning the models and datasets that our reporting depends on, with an emphasis on solutions that keep working without constant attention.
Data Pipeline Development & Integration · Design, build, and maintain scalable data pipelines and data integration workflows using Microsoft Azure services such as Data Factory, Synapse Analytics, Azure Databricks, and related technologies. · Develop and maintain ETL/ELT processes that support business reporting, analytics, and machine learning.
· Collaborate with data architects, analysts, and business stakeholders to gather requirements and deliver data solutions aligned with business goals. · Support the migration and modernization of legacy data systems into Azure and Microsoft Fabric environments. · Translate technical options and trade-offs into terms business stakeholders can act on.
Required Education and Experience · Bachelor's degree in computer science, Data Engineering, Information Systems, or a related field preferred (or equivalent experience). · At least 3 years of experience as a Data Engineer, ideally in professional services or large enterprise environments. · Demonstrable expertise in building data pipelines and cloud data solutions on Azure. · Experience with Microsoft Fabric is strongly preferred. Technical Skills
Tools & Technology · Microsoft Fabric and the Azure data platform (Data Factory, Synapse Analytics, Data Lake, Databricks).· Power BI and Microsoft 365 (Teams, SharePoint, Excel). · Source control and deployment tooling (e.g., Git, Azure DevOps). Mindset
· Organize data in OneLake using a layered approach that keeps raw, enriched, and curated data clearly separated and traceable. · Develop and maintain curated datasets and semantic models that support Power BI reporting and self-service analysis. · Monitor capacity, refresh schedules, and job performance, and tune them as adoption and data volumes grow.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Day 33
Similar jobs usually come down between day 6 and day 56.
From 13,338 similar postings that came down. Coming down is not always a hire.
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Check the employer’s posting for the current role and application details.
Already applied? Track this application
Yes. We’ve followed 3 other Data Engineer jobs there since October 2026. All 3 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Description
Data Engineer
Location: In one of NAC's 4 offices (Columbus, Los Angeles, Seattle, or Spokane)
Department: Information Technology
Reports To: Data Leader
Position OverviewNAC is looking for an experienced Data Engineer to join our delivery team, with a specific focus on designing, building, and optimizing data solutions on Microsoft Azure and Microsoft Fabric. This role is critical to helping NAC unlock the full value of our data assets, supporting advanced analytics, reporting, and digital transformation across the firm.
The ideal candidate is confident working with a modern data stack, automating data pipelines, and delivering reliable, scalable, high-quality data solutions in enterprise environments. The day-to-day work ranges from ingesting data out of firm business systems into a governed lakehouse to tuning the models and datasets that our reporting depends on, with an emphasis on solutions that keep working without constant attention.
This position reports to our Data Leader and will work closely with IT leadership and the data team, as well as resources supporting data architecture and data governance.
Key Responsibilities:· Design, build, and maintain scalable data pipelines and data integration workflows using Microsoft Azure services such as Data Factory, Synapse Analytics, Azure Databricks, and related technologies.
· Develop and maintain ETL/ELT processes that support business reporting, analytics, and machine learning.
· Build ingestion patterns for a range of sources, including business applications, APIs, relational databases, and file-based feeds.
· Implement scheduling, orchestration, automation, and error handling so recurring data loads run reliably with minimal manual intervention.
· Implement and support Microsoft Fabric solutions, including dataflows, lakehouses, data warehouses, and real-time analytics features.
· Organize data in OneLake using a layered approach that keeps raw, enriched, and curated data clearly separated and traceable.
· Develop and maintain curated datasets and semantic models that support Power BI reporting and self-service analysis.
· Monitor capacity, refresh schedules, and job performance, and tune them as adoption and data volumes grow.
· Optimize data architectures for performance, reliability, and cost efficiency in cloud environments.
· Apply dimensional modeling and other established modeling patterns so data is understandable, reusable, and consistent across reporting.
· Write and tune advanced SQL, along with Python or PySpark notebooks, for complex transformation work.
· Monitor, troubleshoot, and improve data workflows, resolving failures and performance bottlenecks at the source rather than working around them.
· Ensure high-quality, secure, and compliant data management practices in line with firm policy, client contractual obligations, and applicable data protection regulations.
· Implement data quality rules, validation, and monitoring so issues are caught before they reach reporting or decision-making.
· Apply access controls, sensitivity handling, and lineage practices in partnership with the resources supporting data governance.
· Collaborate with data architects, analysts, and business stakeholders to gather requirements and deliver data solutions aligned with business goals.
· Support the migration and modernization of legacy data systems into Azure and Microsoft Fabric environments.
· Translate technical options and trade-offs into terms business stakeholders can act on.
· Produce and maintain technical documentation for data pipelines, architecture, and engineering best practices.
· Follow source control and deployment practices, including Git-based development and structured promotion across environments.
Requirements
Qualifications & Skills:
· Bachelor's degree in computer science, Data Engineering, Information Systems, or a related field preferred (or equivalent experience). · At least 3 years of experience as a Data Engineer, ideally in professional services or large enterprise environments. · Demonstrable expertise in building data pipelines and cloud data solutions on Azure. · Experience with Microsoft Fabric is strongly preferred.
· Strong hands-on experience with Microsoft Azure data services (e.g. Data Factory, Synapse Analytics, Data Lake, Databricks).· Direct experience delivering solutions using Microsoft Fabric.· Advanced SQL skills and experience with data modeling, transformation, and integration.· Knowledge of Python or other scripting languages is an advantage.· Familiarity with data governance, data quality, and compliance frameworks.· Certification in Microsoft Azure data engineering or Microsoft Fabric is a plus.
· Excellent communication skills, able to translate technical solutions into business value. · Ability to work independently and collaboratively in a fast-paced, client-facing environment. · Comfortable working across teams and explaining technical concepts to non-technical audiences.
· Microsoft Fabric and the Azure data platform (Data Factory, Synapse Analytics, Data Lake, Databricks).· Power BI and Microsoft 365 (Teams, SharePoint, Excel). · Source control and deployment tooling (e.g., Git, Azure DevOps).
· Proactive, resourceful, and adaptable. · Committed to continuous improvement, automation, and reducing manual effort over time.
· Collaborative, service-oriented mindset with the ability to work across teams. · Strong analytical, organizational, and problem-solving abilities.· High degree of empathy and customer orientation. · Ability to meet deadlines, manage priorities, and deliver initiatives successfully.
· Professional open-office environment with collaborative work areas and shared resources.
· Hand/wrist/finger dexterity for 8 hours a day, 40 hours per week. · Ability to sit for long periods of time.
· Full-time, minimum expectation of 40 hours per week.
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Columbus
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