About this opportunity
Career Category
Engineering
Job Description
Level 4 Data Engineer:
What you will do
Let’s do this. Let’s change the world. In this vital role you will be responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and performing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has deep technical skills, experience with database technologies, and a deep understanding of data architecture and ETL processes.
Roles & Responsibilities:
Design, develop, and maintain data solutions for data generation, collection, and processing
Be a crucial team member that assists in design and development of the data pipeline
Build data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems
Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions
Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform.
Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks
Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs
Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency
Implement data security and privacy measures to protect sensitive data
Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
Collaborate and communicate effectively with product teams
Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast-paced business needs across geographic regions
Identify and resolve complex data-related challenges
Adhere to best practices for coding, testing, and designing reusable code/component
Explore new tools and technologies that will help to improve ETL platform performance
Participate in sprint planning meetings and provide estimations on technical implementation
What we expect of you
We are all different, yet we all use our unique contributions to serve patients.
Basic Qualifications:
Master’s/ Bachelor's degree and 5 - 9 years of Computer Science, IT or related field experience
Preferred Qualifications:
Must-Have Skills:
Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing
Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools
Excellent problem-solving skills and the ability to work with large, complex datasets
Solid understanding of data governance frameworks, tools, and best practices.
Knowledge of data protection regulations and compliance requirements
Good-to-Have Skills:
Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development
Good understanding of data modeling, data warehousing, and data integration concepts
Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
Hands-on experience designing, developing, and implementing AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search, tokenization, prompt engineering, and AI-assisted development tools such as OpenAI Codex, GitHub Copilot, or equivalent platform.
Professional Certifications
Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)
Soft Skills:
Excellent critical-thinking and problem-solving skills
Good communication and collaboration skills
Demonstrated awareness of how to function in a team setting
Demonstrated presentation skills
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Job details
How this role compares
Computed from every other active Data & Digital role in our database, not just this employer's listings.
We currently track 894 comparable Data & Digital roles across 82 biopharma companies.
Salary context
280 of 894 peers report a salary range (USD, annualized)
Peers share this role's job function. This posting doesn't list a seniority level, so peers aren't narrowed by seniority either -- the range below may span more levels than usual.
Where these roles are based
Top locations among the 894 comparable roles
+ 36 more countries
Seniority mix
580 of 894 peers have a known seniority level
Therapeutic area mix
31 of 894 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
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How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.