2d 20h ago
Senior Data Engineer
azuresparkdbtsqlpower_bi
📡Remote In-Country
|Albania, Andorra, Austria, Senior Data Engineer
Data engineering
2d 20h agoRemote In-Country
Contract
IC
Albania, Andorra, Austria,
Source not independently verified - confirm the company domain before applying.
ID 117616
117617
Data Engineer
Senior
"Customer location: Denmark
Candidates locations: EU
Language: English B2
Estimated start date: 12.10.2026
Duration: 6 months"
Project Responsibilities
Build and maintain multi-layer pipelines (Landing → Raw → Enriched → Curated) on Azure Databricks (Spark, Delta Lake)
Orchestrate pipelines via Databricks Jobs / Workflows: dependencies, retries, alerting
Implement batch and API-based data ingestion from multiple source systems
Apply schema enforcement and handle schema drift; run data quality checks at ingestion
Work hands-on with dbt for pipeline observability and data governance tasks
Monitor job failures, data freshness, and pipeline health against SLA-based delivery targets
Set up alerts, logging, and retry strategies for production pipelines
Work within a controlled Dev/Test/Prod environment: access control, audit trails, pipeline documentation, traceability to requirements
Contribute to CI/CD and MLOps/AI pipelines on Databricks where the project needs it
Candidate's Portrait
This is a senior, independent role: the ideal candidate is comfortable taking ownership with minimal oversight and has a flexible, self-driven mindset.
Must-haves
Strong hands-on experience with Azure Databricks: Spark, Delta Lake
Build and maintain multi-layer pipelines: Landing → Raw → Enriched → Curated
Schema enforcement and schema-drift handling
Data quality checks at ingestion
Orchestration via Databricks Jobs / Workflows: dependencies, retries, alerts
Batch and API-based data ingestion
Strong hands-on experience with dbt
Monitor job failures, data freshness, and pipeline health
SLA-based data delivery
Alerts, logging, and retry strategies
Access control models
Audit trails, lineage, and traceability
Logging and evidence generation
Segregation of duties
Data contracts
Pipeline documentation
Controlled environments (Dev/Test/Prod)
Traceability to requirements
Nice to have
CI/CD & DevOps for Data — Git-based development (branching), CI/CD pipelines for data workflows, promoting code across environments, integrating testing into deployment pipelines
AI/MLOps — MLOps / AI pipelines on Databricks
Exposure to regulatory domains (GxP, clinical trials, pharmacovigilance)
Strong SQL engineering / modular, reusable dbt models, tests, and documentation at Analytics Engineer depth
Dimensional modeling: star schema, OBT, curated marts
Tabular Editor (metadata-as-code concepts)
Power BI dataset structure, performance, and KPI/semantic consistency
Experience in the pharmaceutical or biotechnology industry
117617
Data Engineer
Senior
"Customer location: Denmark
Candidates locations: EU
Language: English B2
Estimated start date: 12.10.2026
Duration: 6 months"
Project Responsibilities
Build and maintain multi-layer pipelines (Landing → Raw → Enriched → Curated) on Azure Databricks (Spark, Delta Lake)
Orchestrate pipelines via Databricks Jobs / Workflows: dependencies, retries, alerting
Implement batch and API-based data ingestion from multiple source systems
Apply schema enforcement and handle schema drift; run data quality checks at ingestion
Work hands-on with dbt for pipeline observability and data governance tasks
Monitor job failures, data freshness, and pipeline health against SLA-based delivery targets
Set up alerts, logging, and retry strategies for production pipelines
Work within a controlled Dev/Test/Prod environment: access control, audit trails, pipeline documentation, traceability to requirements
Contribute to CI/CD and MLOps/AI pipelines on Databricks where the project needs it
Candidate's Portrait
This is a senior, independent role: the ideal candidate is comfortable taking ownership with minimal oversight and has a flexible, self-driven mindset.
Must-haves
Strong hands-on experience with Azure Databricks: Spark, Delta Lake
Build and maintain multi-layer pipelines: Landing → Raw → Enriched → Curated
Schema enforcement and schema-drift handling
Data quality checks at ingestion
Orchestration via Databricks Jobs / Workflows: dependencies, retries, alerts
Batch and API-based data ingestion
Strong hands-on experience with dbt
Monitor job failures, data freshness, and pipeline health
SLA-based data delivery
Alerts, logging, and retry strategies
Access control models
Audit trails, lineage, and traceability
Logging and evidence generation
Segregation of duties
Data contracts
Pipeline documentation
Controlled environments (Dev/Test/Prod)
Traceability to requirements
Nice to have
CI/CD & DevOps for Data — Git-based development (branching), CI/CD pipelines for data workflows, promoting code across environments, integrating testing into deployment pipelines
AI/MLOps — MLOps / AI pipelines on Databricks
Exposure to regulatory domains (GxP, clinical trials, pharmacovigilance)
Strong SQL engineering / modular, reusable dbt models, tests, and documentation at Analytics Engineer depth
Dimensional modeling: star schema, OBT, curated marts
Tabular Editor (metadata-as-code concepts)
Power BI dataset structure, performance, and KPI/semantic consistency
Experience in the pharmaceutical or biotechnology industry
Required Skills
azuresparkdbtsqlpower_bi
Required Languages
🇬🇧 English