Back to jobs

Staff Data Engineer - Data Nexus

Pay
Pay varies by location — pay source
As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location. The salary range for positions that will be physically based in the NYC Metro Area is $135,000-180,000 The salary range for positions that will be physically based in all other locations within the United States is $120,750-161,000.
The salary range for positions that will be physically based in the NYC Metro Area is $135,000-180,000 The salary range for positions that will be physically based in all other locations within the United States is $120,750-161,000. Base pay is one part of the Total Rewards that Medidata provides to compensate and recognize employees for their work. Most sales positions are eligible for a commission on the terms of applicable plan documents, and many of Medidata's non-sales positions are eligible for annual bonuses. Medidata believes that benefits should connect you to the support you need when it matters most and provides benefits, including medical, dental, life and disability insurance, 401(k) matching, family leave, flexible paid time off; and 10 paid holidays per year.
Read the full posting
Work setting
Hybrid — work setting source
Location: This is a hybrid remote/in-office role. Medidata follows a hybrid office policy in which employees who are hired for an in-person position are expected to work on site a certain number of days per week following Company policy.
Read the full posting
Employment
Not stated

Pay by location

Also stated
$135K–$180K
Also stated
$121K–$161K

What you’ll work on

Full posting
  • Lead architecture and build of ingestion, migration, CDC, streaming, and ETL/ELT solutions

  • Lead large-scale clinical study data migrations for customers and third parties

  • Design reusable data products and services for apps, analytics, and AI/ML

  • Mentor engineers and review designs and code

From the employer’s posting
Lead the architecture, design, and implementation of scalable data ingestion, migration, CDC, streaming, and ETL/ELT solutions.
Provide technical leadership for large-scale customer and third-party clinical study data migrations.
Design and build reusable data products and services supporting Medidata applications, analytics, reporting, AI/ML, and customer integrations.
Mentor engineers, review designs and code, and establish engineering patterns and best practices across the team.

What you’ll bring

All qualifications

Core experience

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent practical experience.
  • 8+ years of professional software or data engineering experience, including experience designing and operating large-scale production data systems.
  • Strong understanding of modern data engineering patterns including ETL/ELT, Change Data Capture, streaming, data modeling, data migration, and distributed data processing.
  • Experience with modern cloud data platforms, transformation frameworks, and workflow orchestration technologies such as Snowflake, dbt, Airflow, or comparable platforms.
  • Experience designing and operating cloud-native data solutions on AWS or another major cloud platform.
  • Hands-on experience with streaming and lakehouse technologies such as Apache Flink, Kafka, Apache Iceberg, Amazon S3, and enterprise data catalog technologies such as AWS Glue or comparable platforms.

Preferred experience

  • Experience building AI-enabled data applications and Generative AI use cases such as Retrieval-Augmented Generation (RAG), natural-language-to-SQL, conversational analytics, intelligent data discovery, or semantic search.
  • Experience with LLMs, embeddings, vector databases, metadata enrichment, knowledge retrieval, or similar AI/data architectures.
  • Experience applying AI to data engineering use cases such as automated schema mapping, data transformation generation, data classification, anomaly detection, data-quality analysis, or intelligent pipeline troubleshooting.
  • Experience integrating AI/ML models or agentic workflows with enterprise data platforms, APIs, and production data pipelines.
Qualification wording
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent practical experience.
8+ years of professional software or data engineering experience, including experience designing and operating large-scale production data systems.
Strong understanding of modern data engineering patterns including ETL/ELT, Change Data Capture, streaming, data modeling, data migration, and distributed data processing.
Experience with modern cloud data platforms, transformation frameworks, and workflow orchestration technologies such as Snowflake, dbt, Airflow, or comparable platforms.
Experience designing and operating cloud-native data solutions on AWS or another major cloud platform.
Hands-on experience with streaming and lakehouse technologies such as Apache Flink, Kafka, Apache Iceberg, Amazon S3, and enterprise data catalog technologies such as AWS Glue or comparable platforms.
Experience building AI-enabled data applications and Generative AI use cases such as Retrieval-Augmented Generation (RAG), natural-language-to-SQL, conversational analytics, intelligent data discovery, or semantic search.
Experience with LLMs, embeddings, vector databases, metadata enrichment, knowledge retrieval, or similar AI/data architectures.
Experience applying AI to data engineering use cases such as automated schema mapping, data transformation generation, data classification, anomaly detection, data-quality analysis, or intelligent pipeline troubleshooting.
Experience integrating AI/ML models or agentic workflows with enterprise data platforms, APIs, and production data pipelines.
Education & alternatives
Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent practical experience. - 8+ years of professional software or data engineering experience, including experience designing and operating large-scale production data systems.

About MEDIDATA

Our mission is to make clinical operational data easier to ingest, migrate, transform, govern, and consume at scale.

In the employer’s words · Read in context

Apply at MEDIDATA

Posting record

Report an error

Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 9, 20264 days ago
Recorded sightings
5
Last seen by us
Nov 14, 2026
Employer says posted
Oct 15, 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

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 4

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.

MEDIDATA is hiring

4 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.

  • Java
  • Python
  • Scala
  • SQL
  • AWS
  • dbt
  • Iceberg
  • Kafka
  • Kubernetes
  • S3
  • Snowflake
  • Terraform
  • Airflow
Where the posting names them
- Strong understanding of modern data engineering patterns including ETL/ELT, Change Data Capture, streaming, data modeling, data migration, and distributed data processing. - Strong software engineering fundamentals with proficiency in SQL and experience with languages such as Python, Java, Scala, or equivalent. - Experience with modern cloud data platforms, transformation frameworks, and workflow orchestration technologies such as Snowflake, dbt, Airflow, or comparable platforms.
Preferred Qualifications - Experience building AI-enabled data applications and Generative AI use cases such as Retrieval-Augmented Generation (RAG), natural-language-to-SQL, conversational analytics, intelligent data discovery, or semantic search. - Experience with LLMs, embeddings, vector databases, metadata enrichment, knowledge retrieval, or similar AI/data architectures.
Our mission is to make clinical operational data easier to ingest, migrate, transform, govern, and consume at scale. We build capabilities spanning large-scale customer and third-party study migrations, near-real-time CDC and streaming pipelines, reusable data products, analytics and reporting, and cross-product data integrations. We are modernizing our platform around cloud-native and lakehouse architectures using technologies including AWS, Snowflake, dbt, Airflow, Apache Flink, Amazon S3, AWS Glue, and Apache Iceberg. We treat data as a product and build trusted, reusable capabilities that power Medidata applications, customer integrations, analytics, and emerging AI/ML experiences. Who you are:
- Experience with modern cloud data platforms, transformation frameworks, and workflow orchestration technologies such as Snowflake, dbt, Airflow, or comparable platforms. - Experience designing and operating cloud-native data solutions on AWS or another major cloud platform. - Hands-on experience with streaming and lakehouse technologies such as Apache Flink, Kafka, Apache Iceberg, Amazon S3, and enterprise data catalog technologies such as AWS Glue or comparable platforms.
- Experience designing and operating cloud-native data solutions on AWS or another major cloud platform. - Hands-on experience with streaming and lakehouse technologies such as Apache Flink, Kafka, Apache Iceberg, Amazon S3, and enterprise data catalog technologies such as AWS Glue or comparable platforms. - Strong understanding of scalability, performance, security, data quality, observability, reliability, and production operations.
- Strong software engineering fundamentals with proficiency in SQL and experience with languages such as Python, Java, Scala, or equivalent. - Experience with modern cloud data platforms, transformation frameworks, and workflow orchestration technologies such as Snowflake, dbt, Airflow, or comparable platforms. - Experience designing and operating cloud-native data solutions on AWS or another major cloud platform.
- Experience with large-scale enterprise or clinical data migrations, analytics platforms, APIs, or reusable data products. - Experience with infrastructure automation and modern engineering practices using technologies such as Kubernetes, Terraform, GitHub Actions, or equivalent. - Experience in life sciences, healthcare, clinical trials, or another regulated environment.

Your next step

Complete your application on www.3ds.com. The employer’s form will show what is required.

Already applied? Track this application

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 ↗

Location: This is a hybrid remote/in-office role.

 

Medidata follows a hybrid office policy in which employees who are hired for an in-person position are expected to work on site a certain number of days per week following Company policy.

 

About our Company:

Medidata is powering smarter treatments and healthier people through digital solutions to support clinical trials. Celebrating over 25 years of ground-breaking technological innovation across more than 38,000 trials and 12 million patients, Medidata offers industry-leading expertise, analytics-powered insights, and one of the largest clinical trial data sets in the industry. More than 1 million registered users across approximately 2,300 customers trust Medidata's seamless, end-to-end platform to improve patient experiences, accelerate clinical breakthroughs, and bring therapies to market faster. A Dassault Systèmes brand (Euronext Paris: FR0014003TT8, DSY.PA), Medidata is headquartered in New York City and has been recognized as a Leader by Everest Group and IDC. Discover more at www.medidata.com. Listen to our latest podcast, from Dreamers to Disruptors, and follow us at @Medidata.

Our Team

The Data Nexus team within Medidata Study Experience builds the modern data foundation that connects clinical applications, customer data, analytics, and enterprise integrations.

Our mission is to make clinical operational data easier to ingest, migrate, transform, govern, and consume at scale. We build capabilities spanning large-scale customer and third-party study migrations, near-real-time CDC and streaming pipelines, reusable data products, analytics and reporting, and cross-product data integrations.

We are modernizing our platform around cloud-native and lakehouse architectures using technologies including AWS, Snowflake, dbt, Airflow, Apache Flink, Amazon S3, AWS Glue, and Apache Iceberg. We treat data as a product and build trusted, reusable capabilities that power Medidata applications, customer integrations, analytics, and emerging AI/ML experiences.

Who you are:

As a Staff Data Engineer, you will be a hands-on technical leader responsible for solving complex data engineering problems, influencing architecture and technical direction, driving strategic initiatives across teams, and raising engineering standards across Data Nexus.

What You'll Do

  • Lead the architecture, design, and implementation of scalable data ingestion, migration, CDC, streaming, and ETL/ELT solutions.
  • Provide technical leadership for large-scale customer and third-party clinical study data migrations.
  • Design and build reusable data products and services supporting Medidata applications, analytics, reporting, AI/ML, and customer integrations.
  • Drive modernization across cloud data warehousing, workflow orchestration, streaming, and lakehouse architectures.
  • Design scalable data models, transformation frameworks, APIs, and integration patterns for complex operational and analytical workloads.
  • Improve data quality, observability, performance, reliability, security, and cost efficiency across the platform.
  • Lead technical design and architecture discussions and collaborate across Product, Engineering, QA, Architecture, and other teams to deliver complex initiatives.
  • Mentor engineers, review designs and code, and establish engineering patterns and best practices across the team.
  • Leverage AI-assisted engineering tools such as GitHub Copilot, Claude Code, Cursor, and similar technologies to accelerate development, refactoring, testing, troubleshooting, and documentation.
  • Identify opportunities to apply Generative AI and intelligent data experiences to improve how users discover, understand, and interact with clinical data.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent practical experience.
  • 8+ years of professional software or data engineering experience, including experience designing and operating large-scale production data systems.
  • Strong understanding of modern data engineering patterns including ETL/ELT, Change Data Capture, streaming, data modeling, data migration, and distributed data processing.
  • Strong software engineering fundamentals with proficiency in SQL and experience with languages such as Python, Java, Scala, or equivalent.
  • Experience with modern cloud data platforms, transformation frameworks, and workflow orchestration technologies such as Snowflake, dbt, Airflow, or comparable platforms.
  • Experience designing and operating cloud-native data solutions on AWS or another major cloud platform.
  • Hands-on experience with streaming and lakehouse technologies such as Apache Flink, Kafka, Apache Iceberg, Amazon S3, and enterprise data catalog technologies such as AWS Glue or comparable platforms.
  • Strong understanding of scalability, performance, security, data quality, observability, reliability, and production operations.
  • Demonstrated ability to lead complex technical initiatives spanning multiple applications, systems, and engineering teams.
  • Strong communication and technical leadership skills, including mentoring engineers and influencing architectural and engineering decisions.
  • Practical experience incorporating AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or equivalent tools into software engineering workflows.

Preferred Qualifications

  • Experience building AI-enabled data applications and Generative AI use cases such as Retrieval-Augmented Generation (RAG), natural-language-to-SQL, conversational analytics, intelligent data discovery, or semantic search.
  • Experience with LLMs, embeddings, vector databases, metadata enrichment, knowledge retrieval, or similar AI/data architectures.
  • Experience applying AI to data engineering use cases such as automated schema mapping, data transformation generation, data classification, anomaly detection, data-quality analysis, or intelligent pipeline troubleshooting.
  • Experience integrating AI/ML models or agentic workflows with enterprise data platforms, APIs, and production data pipelines.
  • Familiarity with AI platform concepts such as model gateways, MCP, prompt and context management, evaluation, observability, security, and responsible AI practices.
  • Experience with large-scale enterprise or clinical data migrations, analytics platforms, APIs, or reusable data products.
  • Experience with infrastructure automation and modern engineering practices using technologies such as Kubernetes, Terraform, GitHub Actions, or equivalent.
  • Experience in life sciences, healthcare, clinical trials, or another regulated environment.

As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location.

  • The salary range for positions that will be physically based in the NYC Metro Area is $135,000-180,000
  • The salary range for positions that will be physically based in all other locations within the United States is $120,750-161,000.

 

Base pay is one part of the Total Rewards that Medidata provides to compensate and recognize employees for their work. Most sales positions are eligible for a commission on the terms of applicable plan documents, and many of Medidata's non-sales positions are eligible for annual bonuses. Medidata believes that benefits should connect you to the support you need when it matters most and provides benefits, including medical, dental, life and disability insurance, 401(k) matching, family leave, flexible paid time off; and 10 paid holidays per year.

 

#LI-MM1

#LI-Hybrid

 

Equal Employment Opportunity:

In order to provide equal employment and advancement opportunities to all individuals, employment decisions at Medidata are based on merit, qualifications and abilities. Medidata is committed to a policy of non-discrimination and equal opportunity for all employees and qualified applicants without regard to race, color, religion, gender, sex (including pregnancy, childbirth or medical or common conditions related to pregnancy or childbirth), sexual orientation, gender identity, gender expression, marital status, familial status, national origin, ancestry, age, disability, veteran status, military service, application for military service, genetic information, receipt of free medical care, or any other characteristic protected under applicable law. Medidata will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

 

We will accept applications on an ongoing basis until we fill the position.

 

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
As with all roles, Medidata sets ranges based on a number of factors including function, level, candidate expertise and experience, and geographic location. The salary range for positions that will be physically based in the NYC Metro Area is $135,000-180,000 The salary range for positions that will be physically based in all other locations within the United States is $120,750-161,000.
More source context
The salary range for positions that will be physically based in the NYC Metro Area is $135,000-180,000 The salary range for positions that will be physically based in all other locations within the United States is $120,750-161,000. Base pay is one part of the Total Rewards that Medidata provides to compensate and recognize employees for their work. Most sales positions are eligible for a commission on the terms of applicable plan documents, and many of Medidata's non-sales positions are eligible for annual bonuses. Medidata believes that benefits should connect you to the support you need when it matters most and provides benefits, including medical, dental, life and disability insurance, 401(k) matching, family leave, flexible paid time off; and 10 paid holidays per year.
Location & working pattern

United States, NY, New York

Location: This is a hybrid remote/in-office role. Medidata follows a hybrid office policy in which employees who are hired for an in-person position are expected to work on site a certain number of days per week following Company policy. About our Company:
More source context
#LI-MM1 #LI-Hybrid Equal Employment Opportunity:
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.