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Senior Data Engineer

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Avantor is looking for a dynamic, forward-thinking, and experienced Senior Data Engineer, delivering results against some of the most complex business and technology initiatives. This role will be a full-time position based out of our Pune or Coimbatore office. If you are passionate about solving complex challenges and driving innovation – let's talk!
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Own the end-to-end pipeline: Fivetran ingestion, dbt transformation, Snowflake modeling, Power BI consumption

  • Lead data engineering initiatives and mentor junior engineers

  • Gather requirements from business stakeholders and design scalable pipelines and data models

  • Prototype new data solutions with the Analytics and BI teams, including GenAI-assisted approaches

  • Set engineering standards for dbt style, naming, and testing coverage

From the employer’s posting
Own the end-to-end data pipeline lifecycle: ingestion (Fivetran) → transformation (dbt) → storage/modeling (Snowflake) → consumption (Power BI).
Lead development and execution of data engineering initiatives across specific projects, mentoring junior engineers on best practices.
Ability to engage directly with business stakeholders, gather requirements, and work independently to translate them into scalable pipeline/data model designs.
Collaborate with the Analytics and BI teams to prototype and prove the viability of new data solutions, including GenAI-assisted approaches where applicable.
Provide technical leadership in the development of engineering standards (dbt style guides, naming conventions, testing coverage expectations).

What you’ll bring

All qualifications

Core experience

  • 10–12 years of overall experience in IT, with a strong focus on data engineering and cloud data platforms.
  • 5+ years of experience with Python for data engineering (scripting, automation, orchestration).
  • Expertise in designing data models (dimensional modeling, star/snowflake schemas) for both operational reporting and self-service analytics.
  • 6+ years of architecture or engineering experience in data modeling, building data pipelines, ELT/ETL frameworks, data products, and distributed data systems.
  • Experience with PySpark for large-scale data processing.
  • Experience enabling Power BI consumption layers — building/optimizing Snowflake views or dbt marts specifically for BI performance.

Preferred experience

  • Bachelor's degree in Engineering (Computer Science or other equivalent majors).
  • Ability to work independently with minimal supervision while collaborating cross-functionally with product owners, business stakeholders, and management.
Qualification wording
10–12 years of overall experience in IT, with a strong focus on data engineering and cloud data platforms.
5+ years of experience with Python for data engineering (scripting, automation, orchestration).
Expertise in designing data models (dimensional modeling, star/snowflake schemas) for both operational reporting and self-service analytics.
6+ years of architecture or engineering experience in data modeling, building data pipelines, ELT/ETL frameworks, data products, and distributed data systems.
Experience with PySpark for large-scale data processing.
Experience enabling Power BI consumption layers — building/optimizing Snowflake views or dbt marts specifically for BI performance.
Bachelor's degree in Engineering (Computer Science or other equivalent majors).
Ability to work independently with minimal supervision while collaborating cross-functionally with product owners, business stakeholders, and management.
Apply at VWR International

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Live
First seen by us
Sep 30, 202635 days ago
Recorded sightings
101
Last seen by us
Nov 4, 2026

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How this job compares

Time since we first saw it

Day 35

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From 10,733 similar postings that came down. Coming down is not always a hire.

VWR International is hiring

7 open jobs

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

  • Hiring has slowed
  • Takes jobs down at a usual pace
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.

  • Python
  • SQL
  • AWS
  • Azure
  • dbt
  • Fivetran
  • Power BI
  • SAP
  • Snowflake
  • Airflow
  • Dagster
  • PySpark
Where the posting names them
Nice to have: - 5+ years of experience with Python for data engineering (scripting, automation, orchestration). - Experience with PySpark for large-scale data processing.
- 3+ years of experience enabling or supporting BI/reporting layers using Power BI — including semantic modeling, DAX, and performance optimization of datasets feeding dashboards. - Exposure to or working knowledge of Generative AI concepts and tools (LLM-based data documentation/cataloging, natural-language-to-SQL tools, AI-assisted data quality or anomaly detection, Copilot-style dev tooling) — hands-on production experience is a plus, not mandatory. Nice to have:
- Exposure to orchestration tools (Airflow, Dagster, or Snowflake Tasks/Streams). - Familiarity with using LLMs/GenAI APIs (OpenAI, Azure OpenAI, AWS Bedrock) to accelerate data engineering workflows — e.g., auto-generating dbt documentation, AI-assisted SQL/data quality checks, or building lightweight natural-language query interfaces over Snowflake. THOSE NECESSARY TO PERFORM THE JOB COMPETENTLY:
- Experience enabling Power BI consumption layers — building/optimizing Snowflake views or dbt marts specifically for BI performance. - Very good analytical skills to independently analyze and resolve ELT, SQL, and pipeline issues. - Ability to provide effort estimation for data engineering initiatives.
- Provide technical leadership in the development of engineering standards (dbt style guides, naming conventions, testing coverage expectations). - Comfortable with rapid prototyping and disciplined software development practices (version control, CI/CD, code review for dbt/SQL). - Perform other duties as assigned.
CERTIFICATIONS: Preferred SnowPro Core and/or SnowPro Advanced certifications. dbt Certification (Analytics Engineer) is a plus. EXPERIENCE:
- 6+ years of experience within Data Warehousing: management (star schemas, snowflake schemas, dimensional modeling) within Snowflake. - 4+ years of hands-on experience with dbt (data build tool) — building and maintaining modular transformation layers, testing frameworks, macros, and documentation (dbt docs/lineage). - 3+ years of hands-on experience with Fivetran (or similar managed ELT/connector tools) for automated data ingestion from SaaS, ERP, and database sources.
- Thorough knowledge of Snowflake architecture (virtual warehouses, micro-partitioning, clustering, cost/performance optimization). - Strong hands-on experience building and maintaining dbt projects — models, tests, snapshots, incremental strategies, and CI/CD integration for dbt deployments. - Strong hands-on experience configuring and managing Fivetran connectors, sync schedules, transformations, and troubleshooting ingestion failures.
- Working knowledge of SAP systems as a source system (SAP ECC/S4HANA extraction patterns), integrated via Fivetran or custom pipelines into Snowflake. - Experience enabling Power BI consumption layers — building/optimizing Snowflake views or dbt marts specifically for BI performance. - Very good analytical skills to independently analyze and resolve ELT, SQL, and pipeline issues.
- Collaborate with the Analytics and BI teams to prototype and prove the viability of new data solutions, including GenAI-assisted approaches where applicable. - Own the end-to-end data pipeline lifecycle: ingestion (Fivetran) → transformation (dbt) → storage/modeling (Snowflake) → consumption (Power BI). - Lead development and execution of data engineering initiatives across specific projects, mentoring junior engineers on best practices.
- Lead development and execution of data engineering initiatives across specific projects, mentoring junior engineers on best practices. - Be hands-on in Snowflake development, dbt model design, and Fivetran pipeline configuration/administration. - Explore and pilot GenAI use cases that improve data engineering productivity — e.g., AI-assisted documentation, automated test generation, or natural-language querying over the Snowflake warehouse.
- Ability to work independently with minimal supervision while collaborating cross-functionally with product owners, business stakeholders, and management. - Provide technical leadership in the development of engineering standards (dbt style guides, naming conventions, testing coverage expectations). - Comfortable with rapid prototyping and disciplined software development practices (version control, CI/CD, code review for dbt/SQL).
- 4+ years of hands-on experience with dbt (data build tool) — building and maintaining modular transformation layers, testing frameworks, macros, and documentation (dbt docs/lineage). - 3+ years of hands-on experience with Fivetran (or similar managed ELT/connector tools) for automated data ingestion from SaaS, ERP, and database sources. - 3+ years of experience enabling or supporting BI/reporting layers using Power BI — including semantic modeling, DAX, and performance optimization of datasets feeding dashboards.
- Strong hands-on experience building and maintaining dbt projects — models, tests, snapshots, incremental strategies, and CI/CD integration for dbt deployments. - Strong hands-on experience configuring and managing Fivetran connectors, sync schedules, transformations, and troubleshooting ingestion failures. - Expertise in designing data models (dimensional modeling, star/snowflake schemas) for both operational reporting and self-service analytics.
- Should have worked on preparation of Technical Specification documents and data pipeline design documentation. - Working knowledge of SAP systems as a source system (SAP ECC/S4HANA extraction patterns), integrated via Fivetran or custom pipelines into Snowflake. - Experience enabling Power BI consumption layers — building/optimizing Snowflake views or dbt marts specifically for BI performance.
- 3+ years of hands-on experience with Fivetran (or similar managed ELT/connector tools) for automated data ingestion from SaaS, ERP, and database sources. - 3+ years of experience enabling or supporting BI/reporting layers using Power BI — including semantic modeling, DAX, and performance optimization of datasets feeding dashboards. - Exposure to or working knowledge of Generative AI concepts and tools (LLM-based data documentation/cataloging, natural-language-to-SQL tools, AI-assisted data quality or anomaly detection, Copilot-style dev tooling) — hands-on production experience is a plus, not mandatory.
- Curiosity and practical interest in applying GenAI/LLM capabilities to modernize data engineering workflows (e.g., automated documentation, natural-language interfaces, intelligent data quality monitoring). - SAP functional knowledge is good to have. PREFERRED QUALIFICATIONS:
- 6+ years of architecture or engineering experience in data modeling, building data pipelines, ELT/ETL frameworks, data products, and distributed data systems. - 6+ years of experience within Data Warehousing: management (star schemas, snowflake schemas, dimensional modeling) within Snowflake. - 4+ years of hands-on experience with dbt (data build tool) — building and maintaining modular transformation layers, testing frameworks, macros, and documentation (dbt docs/lineage).
- Experience processing semi-structured data (JSON, Parquet, Avro). - Exposure to orchestration tools (Airflow, Dagster, or Snowflake Tasks/Streams). - Familiarity with using LLMs/GenAI APIs (OpenAI, Azure OpenAI, AWS Bedrock) to accelerate data engineering workflows — e.g., auto-generating dbt documentation, AI-assisted SQL/data quality checks, or building lightweight natural-language query interfaces over Snowflake.
THOSE NECESSARY TO PERFORM THE JOB COMPETENTLY: - Thorough knowledge of Snowflake architecture (virtual warehouses, micro-partitioning, clustering, cost/performance optimization). - Strong hands-on experience building and maintaining dbt projects — models, tests, snapshots, incremental strategies, and CI/CD integration for dbt deployments.
- Be hands-on in Snowflake development, dbt model design, and Fivetran pipeline configuration/administration. - Explore and pilot GenAI use cases that improve data engineering productivity — e.g., AI-assisted documentation, automated test generation, or natural-language querying over the Snowflake warehouse. - Ability to work independently with minimal supervision while collaborating cross-functionally with product owners, business stakeholders, and management.
- 5+ years of experience with Python for data engineering (scripting, automation, orchestration). - Experience with PySpark for large-scale data processing. - Experience processing semi-structured data (JSON, Parquet, Avro).

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Has VWR International posted this job before?

Yes. We’ve followed 2 other Senior Data Engineer jobs there since August 2026. One came down after 6 days. One is still up.

  1. Ind-PuneCame down after 6 days, first seen Aug 28
  2. PuneStill up after 62 days, first seen Sep 3
  3. This jobUp 35 days so far, first seen Sep 30

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 ↗

The Opportunity:

Avantor is looking for a dynamic, forward-thinking, and experienced Senior Data Engineer, delivering results against some of the most complex business and technology initiatives.

This role will be a full-time position based out of our Pune or Coimbatore office.

If you are passionate about solving complex challenges and driving innovation – let's talk!

Our organization is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

The Senior Data Engineer drives data-driven strategies and delivers impactful insights to optimize data platforms, analytics enablement, and business decision-making. This role requires strong engineering depth across modern ELT tooling, analytical expertise, strategic thinking, and the ability to mentor and lead within a cross-functional team.

Job Description

WHAT WE'RE LOOKING FOR:

CERTIFICATIONS:

Preferred SnowPro Core and/or SnowPro Advanced certifications. dbt Certification (Analytics Engineer) is a plus.

EXPERIENCE:

  • 10–12 years of overall experience in IT, with a strong focus on data engineering and cloud data platforms.
  • 6+ years of architecture or engineering experience in data modeling, building data pipelines, ELT/ETL frameworks, data products, and distributed data systems.
  • 6+ years of experience within Data Warehousing: management (star schemas, snowflake schemas, dimensional modeling) within Snowflake.
  • 4+ years of hands-on experience with dbt (data build tool) — building and maintaining modular transformation layers, testing frameworks, macros, and documentation (dbt docs/lineage).
  • 3+ years of hands-on experience with Fivetran (or similar managed ELT/connector tools) for automated data ingestion from SaaS, ERP, and database sources.
  • 3+ years of experience enabling or supporting BI/reporting layers using Power BI — including semantic modeling, DAX, and performance optimization of datasets feeding dashboards.
  • Exposure to or working knowledge of Generative AI concepts and tools (LLM-based data documentation/cataloging, natural-language-to-SQL tools, AI-assisted data quality or anomaly detection, Copilot-style dev tooling) — hands-on production experience is a plus, not mandatory.

Nice to have:

  • 5+ years of experience with Python for data engineering (scripting, automation, orchestration).
  • Experience with PySpark for large-scale data processing.
  • Experience processing semi-structured data (JSON, Parquet, Avro).
  • Exposure to orchestration tools (Airflow, Dagster, or Snowflake Tasks/Streams).
  • Familiarity with using LLMs/GenAI APIs (OpenAI, Azure OpenAI, AWS Bedrock) to accelerate data engineering workflows — e.g., auto-generating dbt documentation, AI-assisted SQL/data quality checks, or building lightweight natural-language query interfaces over Snowflake.

THOSE NECESSARY TO PERFORM THE JOB COMPETENTLY:

  • Thorough knowledge of Snowflake architecture (virtual warehouses, micro-partitioning, clustering, cost/performance optimization).
  • Strong hands-on experience building and maintaining dbt projects — models, tests, snapshots, incremental strategies, and CI/CD integration for dbt deployments.
  • Strong hands-on experience configuring and managing Fivetran connectors, sync schedules, transformations, and troubleshooting ingestion failures.
  • Expertise in designing data models (dimensional modeling, star/snowflake schemas) for both operational reporting and self-service analytics.
  • Should have worked on preparation of Technical Specification documents and data pipeline design documentation.
  • Working knowledge of SAP systems as a source system (SAP ECC/S4HANA extraction patterns), integrated via Fivetran or custom pipelines into Snowflake.
  • Experience enabling Power BI consumption layers — building/optimizing Snowflake views or dbt marts specifically for BI performance.
  • Very good analytical skills to independently analyze and resolve ELT, SQL, and pipeline issues.
  • Ability to provide effort estimation for data engineering initiatives.
  • Ability to engage directly with business stakeholders, gather requirements, and work independently to translate them into scalable pipeline/data model designs.
  • Advanced knowledge of data warehousing concepts and schema design trade-offs.
  • Curiosity and practical interest in applying GenAI/LLM capabilities to modernize data engineering workflows (e.g., automated documentation, natural-language interfaces, intelligent data quality monitoring).
  • SAP functional knowledge is good to have.

PREFERRED QUALIFICATIONS:

Bachelor's degree in Engineering (Computer Science or other equivalent majors).

HOW YOU WILL THRIVE AND CREATE AN IMPACT:

  • Collaborate with the Analytics and BI teams to prototype and prove the viability of new data solutions, including GenAI-assisted approaches where applicable.
  • Own the end-to-end data pipeline lifecycle: ingestion (Fivetran) → transformation (dbt) → storage/modeling (Snowflake) → consumption (Power BI).
  • Lead development and execution of data engineering initiatives across specific projects, mentoring junior engineers on best practices.
  • Be hands-on in Snowflake development, dbt model design, and Fivetran pipeline configuration/administration.
  • Explore and pilot GenAI use cases that improve data engineering productivity — e.g., AI-assisted documentation, automated test generation, or natural-language querying over the Snowflake warehouse.
  • Ability to work independently with minimal supervision while collaborating cross-functionally with product owners, business stakeholders, and management.
  • Provide technical leadership in the development of engineering standards (dbt style guides, naming conventions, testing coverage expectations).
  • Comfortable with rapid prototyping and disciplined software development practices (version control, CI/CD, code review for dbt/SQL).
  • Perform other duties as assigned.

 

Disclaimer:
The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of employees assigned to this position. Avantor is proud to be an equal opportunity employer.

Why Avantor?

Dare to go further in your career. Join our global team of 14,000+ associates whose passion for discovery and determination to overcome challenges relentlessly advances life-changing science.
 
The work we do changes people's lives for the better. It brings new patient treatments and therapies to market, giving a cancer survivor the chance to walk his daughter down the aisle. It enables medical devices that help a little boy hear his mom's voice for the first time. Outcomes such as these create unlimited opportunities for you to contribute your talents, learn new skills and grow your career at Avantor.
 
We are committed to helping you on this journey through our diverse, equitable and inclusive culture which includes learning experiences to support your career growth and success. At Avantor, dare to go further and see how the impact of your contributions set science in motion to create a better world. Apply today!

EEO Statement:

We are an Equal Employment/Affirmative Action employer and VEVRAA Federal Contractor. We do not discriminate in hiring on the basis of sex, gender identity, sexual orientation, race, color, religious creed, national origin, physical or mental disability, protected Veteran status, or any other characteristic protected by federal, state/province, or local law.

If you need a reasonable accommodation for any part of the employment process, please contact us by email at recruiting@avantorsciences.com and let us know the nature of your request and your contact information. Requests for accommodation will be considered on a case-by-case basis. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.

Privacy Policy:

We will use the personal information that you have submitted to us in order to consider your application for the relevant role.
 

Your privacy is important to us. Please click here for our Privacy Policy which explains the purposes for which we will use your personal information and the ways in which we will handle and retain your information. It also explains the rights you have in relation to your information, and how to contact us with any queries or requests.

3rd party non-solicitation policy:

By submitting candidates without having been formally assigned on and contracted for a specific job requisition by Avantor, or by failing to comply with the Avantor recruitment process, you forfeit any fee on the submitted candidates, regardless of your usual terms and conditions. Avantor works with a preferred supplier list and will take the initiative to engage with recruitment agencies based on its needs and will not be accepting any form of solicitation

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