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Data Engineer Lead (USI9) (2401)

Pay
Pay not listedSimilar roles state $127K–$190K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full Time
From the employer’s posting

What you’ll bring

All qualifications

Core experience

  • Bachelor’s degree in computer science, MIS, engineering, or related field
  • 7 years of significant experience in an enterprise Data engineering role

Preferred experience

  • Structured, Semi-structured, and Unstructured Data Warehousing
Qualification wording
Bachelor’s degree in computer science, MIS, engineering, or related field
7 years of significant experience in an enterprise Data engineering role
Structured, Semi-structured, and Unstructured Data Warehousing
Education & alternatives
MINIMUM REQUIREMENTS: - Bachelor’s degree in computer science, MIS, engineering, or related field - Or an additional 3 years of specific work experience in lieu of degree.
Apply at Vse Aviation

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 12, 2026today
Recorded sightings
1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

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.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 55.

From 13,214 similar postings that came down. Coming down is not always a hire.

Vse Aviation is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • SQL
  • Azure
  • Databricks
  • Kafka
  • Oracle
  • Power BI
  • Snowflake
  • SQL Server
Where the posting names them
- 7 years of significant experience in an enterprise Data engineering role - Strong professional proficiency in SQL - Proven Technical Experience with one or more: Snowflake, Microsoft Fabric, Databricks
- Informatica, Azure Data Factory - MSFT SQL Server, Oracle - Microsoft Azure
Description SUMMARY: We are seeking an experienced enterprise Data Engineer (7-10+ years) for the implementation, maintenance, and support of a next-generation cloud-based enterprise Data Lake / Data Lakehouse environment. The ideal candidate will have extensive cloud data platform experience with leading platforms like Snowflake and/or Microsoft Fabric, and deep knowledge and experience in data architecture and data engineering including: implementation of Medallion data architectures (Bronze/Silver/Gold), Analytics cubes, Star Schemas; construction of enterprise-oriented data models across business domains; establishment of high-performance on-prem, hybrid, and cloud data pipelines, and data integrations across key enterprise data repositories & systems using technologies such as Informatica and Azure Data Factory. This role will also be instrumental in establishing data engineering and governance standards, working closely with business stakeholders to standardize and normalize existing data domains, and ensuring data quality remains a core, go-forward asset. DUTIES & RESPONSIBLITIES:
- Develop robust ingestion frameworks for structured, semi-structured, and streaming data sources. - Build scalable ELT/ETL pipelines using cloud-native technologies and orchestration tools such as Informatica and Azure Data Factory. - Design dimensional models, curated data products, and semantic layers to support business intelligence and advanced analytics.
PREFERRED REQUIREMENTS: - Informatica, Azure Data Factory - MSFT SQL Server, Oracle
- MSFT SQL Server, Oracle - Microsoft Azure - Power BI
- Microsoft Purview - Azure DevOps or GitHub Actions - Kafka or Event Hubs
- Strong professional proficiency in SQL - Proven Technical Experience with one or more: Snowflake, Microsoft Fabric, Databricks - Data Governance, Data Systems Architecture, and Data Modeling
- Azure DevOps or GitHub Actions - Kafka or Event Hubs - REST APIs and modern data integration techniques
- Microsoft Azure - Power BI - Golden Gate / Change Data Capture / Data Streaming

Your next step

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

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.

About the role

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.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

Description

SUMMARY: We are seeking an experienced enterprise Data Engineer (7-10+ years) for the implementation, maintenance, and support of a next-generation cloud-based enterprise Data Lake / Data Lakehouse environment. The ideal candidate will have extensive cloud data platform experience with leading platforms like Snowflake and/or Microsoft Fabric, and deep knowledge and experience in data architecture and data engineering including: implementation of Medallion data architectures (Bronze/Silver/Gold), Analytics cubes, Star Schemas; construction of enterprise-oriented data models across business domains; establishment of high-performance on-prem, hybrid, and cloud data pipelines, and data integrations across key enterprise data repositories & systems using technologies such as Informatica and Azure Data Factory.  This role will also be instrumental in establishing data engineering and governance standards, working closely with business stakeholders to standardize and normalize existing data domains, and ensuring data quality remains a core, go-forward asset.

DUTIES & RESPONSIBLITIES:

  • Design, implementation, and evolution of the organization's enterprise Data Lake/Lakehouse architecture.

  • Design and implement a scalable Medallion Architecture (Bronze, Silver, Gold) to support trusted, reusable data assets.

  • Develop robust ingestion frameworks for structured, semi-structured, and streaming data sources.

  • Build scalable ELT/ETL pipelines using cloud-native technologies and orchestration tools such as Informatica and Azure Data Factory.

  • Design dimensional models, curated data products, and semantic layers to support business intelligence and advanced analytics.

  • Implement data quality, lineage, cataloging, and metadata management best practices.

  • Optimize data storage, query performance, and workload management.

  • Establish CI/CD pipelines and Infrastructure-as-Code practices for data engineering solutions.

  • Collaborate with business stakeholders and application teams to understand data requirements and deliver scalable solutions.

  • Define and help enforce enterprise data engineering standards at with technical and business partners.

  • Partner with security and governance teams to implement role-based security, data privacy, and compliance controls.

MINIMUM REQUIREMENTS: 

  • Bachelor’s degree in computer science, MIS, engineering, or related field 

    • Or an additional 3 years of specific work experience in lieu of degree.

  • 7 years of significant experience in an enterprise Data engineering role

  • Strong professional proficiency in SQL

  • Proven Technical Experience with one or more: Snowflake, Microsoft Fabric, Databricks

  • Data Governance, Data Systems Architecture, and Data Modeling

PREFERRED REQUIREMENTS: 

  • Informatica, Azure Data Factory

  • MSFT SQL Server, Oracle

  • Microsoft Azure 

  • Power BI

  • Golden Gate / Change Data Capture / Data Streaming

  • Aviation/Aerospace ERP

  • Structured, Semi-structured, and Unstructured Data Warehousing

  • Microsoft Purview

  • Azure DevOps or GitHub Actions

  • Kafka or Event Hubs

  • REST APIs and modern data integration techniques

OTHER:  

  • The selected applicant will be subject to a background check and drug testing.

  • Candidates may be required to travel within the US and internationally between 10-25% of time.

  • Candidates must be able to work from a VSE office a minimum of four days per week.

#INDVSE

Source details

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Pay

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Location & working pattern

Miramar, FL 33025

Description SUMMARY: We are seeking an experienced enterprise Data Engineer (7-10+ years) for the implementation, maintenance, and support of a next-generation cloud-based enterprise Data Lake / Data Lakehouse environment. The ideal candidate will have extensive cloud data platform experience with leading platforms like Snowflake and/or Microsoft Fabric, and deep knowledge and experience in data architecture and data engineering including: implementation of Medallion data architectures (Bronze/Silver/Gold), Analytics cubes, Star Schemas; construction of enterprise-oriented data models across business domains; establishment of high-performance on-prem, hybrid, and cloud data pipelines, and data integrations across key enterprise data repositories & systems using technologies such as Informatica and Azure Data Factory. This role will also be instrumental in establishing data engineering and governance standards, working closely with business stakeholders to standardize and normalize existing data domains, and ensuring data quality remains a core, go-forward asset. DUTIES & RESPONSIBLITIES:
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