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Consultant, Data Engineering

Pay
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Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Negotiate schema, freshness SLAs and change notices with upstream domain teams

  • Build and operate connectors and change-data-capture into the lake

  • Own the raw landing layer's structure, partitioning and handoff to the medallion pipeline

  • Detect when sources break, drift or go stale before downstream systems do

  • Keep provenance attached to every record from the moment it arrives

From the employer’s posting
Negotiate schema, freshness SLAs, and change-notice with upstream domain teams
Build and operate the connectors and change-data-capture that land upstream sources into the lake
Own the raw landing layer - structure, partitioning, and a clean handoff to the medallion pipeline
Know when a source breaks, drifts, or goes stale - before anything downstream does
provenance travels with every record from the moment it arrives

What you’ll bring

All qualifications

Core experience

  • Strong Python - your primary language for building and operating pipelines, connectors, and tooling.
  • Proven experience handling data at high volume, with real attention to cost, partitioning, and performance.

Preferred experience

  • Bachelor’s degree in Computer Science, Data Engineering, or related field; advanced degree preferred.
Qualification wording
Strong Python - your primary language for building and operating pipelines, connectors, and tooling.
A track record of landing diverse upstream sources into a data lake reliably and on their freshness SLA. Proven experience handling data at high volume, with real attention to cost, partitioning, and performance.
Bachelor’s degree in Computer Science, Data Engineering, or related field; advanced degree preferred.
Education & alternatives
Desirable Requirements - Bachelor’s degree in Computer Science, Data Engineering, or related field; advanced degree preferred. - Certifications or vendor credentials for cloud data platforms.
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Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 12, 20261 day ago
Recorded sightings
3
Last seen by us
Nov 14, 2026
Employer says posted
Oct 16, 2026

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

How this job compares

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 6 and day 56.

From 13,630 similar postings that came down. Coming down is not always a hire.

Dell Technologies is hiring

16 open jobs

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

Hiring record

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  • Python
Where the posting names them
- Senior / staff-level, hands-on depth in data sourcing and ingestion - the core discipline of this role. Comes with 12-15 years of experience. - Strong Python - your primary language for building and operating pipelines, connectors, and tooling. - A track record of landing diverse upstream sources into a data lake reliably and on their freshness SLA. Proven experience handling data at high volume, with real attention to cost, partitioning, and performance.

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About Dell Technologies

People
About 97,000 in 2026, down 10% from the year before.Annual report (SEC Form 10-K)
Company
Listed as DELL.

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 ↗

Consultant, Data Engineering 

Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods, and models. What’s more, we are in collaboration with leading academics, industry experts, and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data. 

What you’ll achieve: 

As a Consultant, you will lead high-impact data engineering projects that strengthen ingestion, transformation, and data product delivery. You will improve observability and quality, drive standards adoption, and coordinate readiness for analytics and AI workloads. You will collaborate with stakeholders to deliver scalable solutions, robust documentation, and measurable value. 

Build the pipelines that bring the outside world into the Knowledge & Intelligence layer - the governed knowledge spine that grounds AI agents on verified, provenance-backed facts. You own how data gets in: the contracts with upstream domain teams, the connectors and change-data-capture that move it, and the landing zone it arrives in. This is hands-on data engineering where everything downstream depends on what you bring in - get the source contracts and ingestion solid and every system that reads this data can trust its inputs.

Join us to do the best work of your career and make a profound social impact as a Consultant on our Data Engineering team.

You will: 

  • Source & publishing contracts. Negotiate schema, freshness SLAs, and change-notice with upstream domain teams - and hold them to it. These contracts are what keep the layer trustworthy.

  • Connectors & ingestion. Build and operate the connectors and change-data-capture that land upstream sources into the lake, reliably and on their freshness SLA.

  • The landing zone. Own the raw landing layer - structure, partitioning, and a clean handoff to the medallion pipeline.

  • Ingestion observability. Know when a source breaks, drifts, or goes stale - before anything downstream does.

  • Grounding discipline. Nothing lands ungrounded; provenance travels with every record from the moment it arrives.

Take the first step towards your dream career 

Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role: 

Essential Requirements 

  • Senior / staff-level, hands-on depth in data sourcing and ingestion - the core discipline of this role. Comes with 12-15 years of experience.

  • Strong Python - your primary language for building and operating pipelines, connectors, and tooling.

  • A track record of landing diverse upstream sources into a data lake reliably and on their freshness SLA. Proven experience handling data at high volume, with real attention to cost, partitioning, and performance.

  • A provenance mindset — “where did this come from” travels with every record you land.

  • Strong collaboration and stakeholder communication with upstream domain teams.

 

Desirable Requirements 

  • Bachelor’s degree in Computer Science, Data Engineering, or related field; advanced degree preferred. 

  • Certifications or vendor credentials for cloud data platforms. 

Source details

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Bengaluru, Karnataka, India

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