Technical Lead - Cloud Data Engineering - Snowflake / DBT
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Your role:
Ready to shape the future? As Technical Lead Cloud Data Engineering, you own the technical direction of our Snowflake- and DBT-based data products from design to delivery. You are equally at home reviewing a data model, coaching a colleague, or presenting a design decision to senior management. You guide a cross-functional team, set engineering standards, and translate R&D business requirements into robust, scalable solutions – all while fostering a culture of quality, accountability, and continuous learning.
Your key responsibilities:
Define end-to-end design of cloud data products; establish standards for data quality, security, GxP compliance, and CI/CD; document decisions as Design Decision Records (DDRs).
Oversee implementation by internal and external engineers; provide expertise on Snowflake performance tuning, DBT pipeline design, SQL optimization, and Python-based processing.
Mentor engineers at all levels; manage cross-team dependencies; communicate risks, trade-offs, and status clearly to all stakeholders.
Scope and plan engineering work; balance feature delivery with technical debt; drive CI/CD adoption via Azure DevOps and automated data testing.
Actively contribute to team growth through recruiting, onboarding, and knowledge sharing.
In return, we offer a high-impact role at the forefront of Healthcare R&D data innovation, a strong international engineering culture, flexible working models, and the purpose-driven environment of a global science and technology company.
Who you are:
Leadership & Mindset
Accountable for team outcomes; leads by example and enables others to grow.
Pragmatic: balances engineering excellence with real-world delivery constraints.
Clear communicator across technical and non-technical audiences.
Experience & Qualifications
Master's degree in Computer Science, Information Technology, or equivalent.
8+ years of hands-on data engineering experience, including significant technical lead responsibility.
Deep expertise in Snowflake (architecture, performance tuning, data sharing) and DBT (pipeline design, testing, job automation).
Strong proficiency in data modelling: Data Vault 2.0, OLAP/OLTP, and semantic ontologies.
Advanced SQL and solid Python skills for data transformation and system integration.
Proven CI/CD experience with Azure DevOps and Git; IaC with Terraform or CloudFormation is a plus.
Familiarity with AWS data services (Glue, Step Functions, Athena, Lambda) is advantageous.
Experience with GxP-compliant data products in a regulated (pharma/healthcare) environment is a strong plus.
Business-fluent English (written and spoken)
Todos los candidatos internos, sin importar si trabajan a tiempo completo o parcial, tendrán la oportunidad de ser considerados para las vacantes disponibles
HC-HF-IRHE Engineering
RL Exp ert 3
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 270 comparable Data & Digital roles across 46 biopharma companies.
Salary context
79 of 270 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 270 comparable roles
+ 11 more countries
Seniority mix
161 of 270 peers have a known seniority level
Therapeutic area mix
4 of 270 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.