Senior Data Engineer – Full-time

keleya digital-health solutions

. Map the current data landscape, including legacy systems, acquired sources, pipelines and dependencies .

Posted 10/8/2026full-timeBerlin • GermanySenior💰 €70,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and maintaining scalable ETL/ELT pipelines using SQL, Python, and PostgreSQL, while ensuring data quality and compliance with GDPR. Proven ability to collaborate across teams and deliver actionable insights through effective data architecture and integration.

Highest-signal resume keywords

SQLPythonPostgreSQLAWS (EC2/RDS)Data Pipeline Architecture

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

ETL/ELT Pipeline DevelopmentData ModellingData Quality PracticesAPI IntegrationWorkflow Automation

Soft Skills

CuriosityOwnershipCollaboration

Tools & Technologies

GitHubAWS QuicksightAirflowDagsterDbt

Industry Keywords

GDPR ComplianceData PrivacyData Landscape MappingData WarehouseVersion Control

Tech Stack

Tools & technologies

AirflowAWSCloudEC2ETLPostgresPythonSQL

About the role

Key responsibilities & impact

Map the current data landscape, including legacy systems, acquired sources, pipelines and dependencies
Define and share a target architecture and migration plan
Design, build and maintain scalable ETL/ELT pipelines using SQL, Python and PostgreSQL
Own and evolve cloud data infrastructure on AWS, primarily EC2 and RDS
Engineer the automated insurance invoicing pipeline for reimbursement, claim-status and financial data
Build ingestion pipelines connecting product, web, CRM and advertising platforms such as Amplitude, Meta, Google Ads and HubSpot
Develop and maintain REST API integrations with internal and external tools and SaaS products
Design data models and warehouse schemas for reporting, product analytics, experimentation and regulatory requirements
Implement data quality, testing, monitoring and alerting
Orchestrate and automate workflows using software engineering best practices, including version control, CI/CD, code review and documentation
Ensure GDPR-compliant handling of health data, including access control, pseudonymisation and retention policies
Collaborate with Marketing, Product and Finance to deliver datasets for tools such as AWS Quicksight
Share knowledge and coach team members on data concepts, tooling and best practices
Migrate key data sources, retire legacy pipelines and tools, and establish the warehouse as the single source of truth

Requirements

What you’ll need

3+ years' experience in Data Engineering or a closely related role
Strong hands-on skills in SQL, Python, PostgreSQL and AWS (EC2/RDS)
Track record of building and owning data pipelines and warehouse architectures from scratch in fast-moving environments
Experience with API integrations, workflow automation and version control (GitHub)
Solid understanding of data modelling, data quality practices and pipeline observability
Awareness of data privacy and security, ideally with experience handling sensitive or regulated data (GDPR)
Nice to have: experience with orchestration tools such as Airflow or Dagster
Nice to have: experience with transformation frameworks such as dbt
Nice to have: infrastructure as code experience
Nice to have: BI tools such as AWS Quicksight
High degree of autonomy, curiosity and ownership
Fluent in English
German is a plus

Benefits

Comp & perks

30 days of paid vacation
Urban Sports Club membership
3 months remote work allowance
Real ownership of the data platform architecture and foundations
Growth through modern data architecture, regulated health data handling, and cross-functional platform ownership
Mentoring and team support
Regular team breakfasts
Fixed celebrations throughout the year
Coaching and knowledge-sharing opportunities