Senior Data Engineer, Clinical Data Platform

Ałmaty
Astana
Belgrad
Erywań
Kluż-Napoka
Kraków
Larnaka
Łódź
Lublin
Remote.Bulgaria
Remote.Georgia
Remote.Kazakhstan
Remote.Poland
Ryga
Sofia
Tbilisi
Warna
Warszawa
Wrocław

Jeśli otrzymałeś tę ofertę pracy od naszych rekruterów, zapoznaj się z naszą Polityką prywatności.

Project overview

You will work on a platform that processes clinical and real-world data (EHRs, labs, registries, trial data) and powers analytics, reporting, and data products for a healthcare / clinical research client.

Position overview

We are looking for a Senior Data Engineer to build and operate a clinical data platform on Databricks, with a strong focus on robust data pipelines, data models, and data quality.

Technology stack

The platform is built on Databricks (Spark, Delta Lake) and includes reusable pipelines, a shared data model, and automated data quality checks.

Responsibilities

Design, build, and maintain end-to-end Databricks data pipelines (ingestion, transformation, publishing) for production use
Work with data models (staging, curated, canonical, or dimensional) and help evolve them together with architects and analysts
Embed data quality and data governance rules into all pipelines (checks, validation, monitoring, alerting)
Optimize Databricks jobs for performance and cost (cluster configuration, partitioning, caching, file layout)
Collaborate with data architects, analysts, and domain experts to clarify requirements and refine technical solutions

Requirements

5+ years of experience in data engineering, DWH, or big data, including production data pipelines
Strong hands-on experience with Databricks: Spark (PySpark/Scala), Delta Lake, Databricks Jobs / Workflows
Proven experience designing and operating end-to-end pipelines on Databricks for batch or near-real-time data
Experience with data pipelines and CI/CD for data
Practical experience with data modeling (layered models, canonical or dimensional models) for analytics and reporting
Experience embedding data quality and data governance rules into pipelines (schema checks, business rules, SLOs, monitoring)
Good communication skills, upper-intermediate or higher English proficiency, and the ability to work closely with stakeholders in distributed teams and communicate directly with clients

Nice to have

Experience designing and delivering PoC solutions on Databricks to quickly validate ideas using real data
Experience with ontologies or a semantic layer (business concepts, metrics, mappings) on top of analytical data

Looking for Similar Opportunities?

Try AI chatbots with our ready-made prompt to discover similar roles that match your skills and interests.

Co oferujemy

Dni wolne

Zgodne z lokalnym prawem

Dbamy o Twoje zdrowie

Zapewniamy szeroki wachlarz usług w ramach prywatnego ubezpieczenia medycznego

Płatne chorobowe

Zgodnie z lokalnym prawem

Wakacje i specjalne dni wolne

Zgodnie z oficjalnym kalendarzem, niezależnie od kalendarza klienta

Komfortowe warunki pracy

Elastyczny czas pracy oraz pomoc w wyposażeniu komfortowego miejsca pracy

Wewnętrzna platforma edukacyjna

Dostęp do profesjonalnych kursów i szkoleń

Wewnętrzne kursy języka angielskiego

Firmowe szkolenia z wysoko wykwalifikowanymi nauczycielami

Równe szanse

Najbardziej poszukiwane

1 of 1

Senior Data Designer

BułgariaCyprŁotwaPolskaRumuniaSerbiaUkraina

Accountable for creating high-quality Enterprise Data Warehouse data designs by understanding and documenting data sources, ingestion methods, mappings, modeling, and defining required data harmonization, calculations, derivations, and transformation logic

Python Data Engineer (Azure), Investment Management

USA

We are seeking a Python Data Engineer (Azure) to join our team. In this role, you will be responsible for creating Microsoft Fabric pipelines and organizing ETL/ELT processes supporting a leading investment management company

Data Quality Engineer, Data Reliability Platform

ArmeniaBułgariaCyprGruzjaŁotwaPolskaRumuniaSerbia

The project includes implementing monitoring rules, building automated validation workflows, and supporting data teams with insights that help maintain data quality at scale