Senior Data Engineer
Obtenga más información sobre las tareas generales relacionadas con esta oportunidad a continuación, así como sobre las habilidades requeridas.
In a few words
Position:
Senior Data Engineer – AI Labs at Insud Pharma
Location:
Madrid (hybrid)
Experience:
5+ years in Data Engineering or Analytics Engineering roles
About AI Labs at Insud Pharma
AI Labs is Insud Pharma’s transversal team for
Artificial Intelligence, Data Science, and Machine Learning
, working across the group to deliver production‑ready data and AI solutions with real impact.
The team operates across a wide range of areas, including
R&D and clinical data, global health and epidemiology, manufacturing and quality, supply chain and operations, and business analytics
, partnering closely with business units, and external organizations.
AI Labs combines strong engineering standards with pragmatic execution, focusing on building scalable AI‑enabled solutions that move from experimentation to real‑world adoption.
Role Context
This role will be
primarily focused on projects linked to Fundación Mundo Sano
, an international organization dedicated to improving health and quality of life for vulnerable communities through research, innovation, and international cooperation (e.g. neglected diseases such as Chagas).
The goal of this position is to ensure that data coming from multiple sources becomes
available, consistent, reliable, and reusable
, enabling dashboards, reporting, and AI/ML use cases.
Due to the international nature of the projects, the role may involve
occasional travel to Latin America, Africa, or other regions
to work closely with local teams and better understand data generation on the ground.
Role Objective
Build and operate a
coherent, well‑structured data foundation
for Fundación Mundo Sano projects by owning the
data engineering layer end‑to‑end
: ingestion, modeling, data quality, availability, monitoring, and data delivery for dashboards and AI enablement.
Key Responsibilities
Build and operate
data ingestion pipelines (ETL/ELT)
from multiple sources (field programs, research datasets, epidemiological surveillance systems, partners, files, APIs).
Design and maintain
data models and curated datasets
that standardize entities, metrics, and definitions across projects.
Ensure
data quality, reliability, and consistency
through automated checks, monitoring, and basic observability.
Decide how data is
structured, stored, and versioned
to enable long‑term reuse and scalability.
Make data
available and easy to consume
for dashboards, reporting, and AI/ML use cases.
Proactively guide business and project teams on data best practices
, setting standards, shaping requirements, and influencing how data should be collected, structured, and used.
Collaborate closely with stakeholders to translate needs into
scalable, maintainable data foundations
.
Technologies (examples – adapt to actual stack)
Languages:
SQL, Python
Pipelines / orchestration:
Airflow, Prefect, Dagster or similar
Transformations:
dbt or equivalent
Storage:
Data warehouse / lakehouse (e.g. Snowflake, BigQuery, Databricks, Synapse)
Data quality / monitoring:
Great Expectations, Soda, or similar
BI / Dashboards:
Power BI, Tableau, Looker or similar
Engineering basics:
Git, CI/CD, basic cloud concepts (AWS / Azure / GCP)
What we are looking for
A senior, hands‑on
Data Engineer
with a strong ownership mindset, comfortable building and operating
core data structures and pipelines
.
5+ years of experience in
Data Engineering or Analytics Engineering
roles.
Strong
SQL
and solid
Python
, with hands‑on experience building and running
ETL/ELT pipelines
in production.
Proven experience integrating
heterogeneous and diverse data sources
(multiple systems, files, APIs, changing schemas, inconsistent identifiers).
Good understanding of
data modeling
and analytical data structures, with the ability to standardize entities, metrics, and definitions across projects.
Experience ensuring
data quality, reliability, and monitoring
, including automated checks and basic observability.
Comfortable making data
available for dashboards, reporting, and AI/ML use cases
through curated, analytics‑ready datasets.
Able to work proactively with business and project teams,
shaping requirements and setting data standards
rather than waiting for fully specified inputs.
Spanish
as the daily working language;
English
required for specific projects and international collaboration.
Pragmatic, ownership‑driven mindset, strong communication skills, and motivation to work on
social and public‑health impact projects
.
Our benefits! xpzdshu
Flexible start time from Monday to Friday
Permanent contract.