Where software concepts come alive™
Senior Data Engineer – Databricks
Location
Poland
Posted
1 day ago
Salary
0
Seniority
Senior
Job Description
Senior Data Engineer – Databricks
Intetics
• Own Databricks production support for the company's data platform, including monitoring, alerting, and incident response across all production data flows. • Maintain and report on SLA performance metrics for data pipeline delivery, ensuring visibility into platform health and accountability across internal and external stakeholders. • Identify and implement pipeline optimizations that reduce Databricks compute costs, improve throughput, and reduce processing windows while tracking impacts through measurable KPIs. • Migrate legacy ETL/ELT pipelines to Databricks, building automation tooling to reduce manual intervention and ensure uninterrupted data delivery during transitions. • Support new customer onboarding by provisioning, validating, and hardening tenant data pipelines that deliver reliable, isolated data from day one. • Design and build high-performance Databricks pipelines that ingest, transform, and serve ERP and CRM data at scale across both Azure and AWS environments. • Own the Delta Lake architecture, including schema design, partitioning strategies, data quality enforcement, and incremental processing patterns. • Enforce data security best practices across Databricks environments, including role-based access control, secrets management, and compliance requirements for enterprise business data. • Implement data quality monitoring and observability across pipeline health and ML model inputs, ensuring data integrity that directly supports predictive analytics. • Apply and enforce multi-tenant data isolation patterns, ensuring reliable and secure data delivery across enterprise customers. • Partner with the Enterprise Architecture team to ensure data pipelines integrate seamlessly with the broader AI and analytics ecosystem. • Support a globally distributed operation through on-call rotation and after-hours incident response, meeting SLAs across multiple time zones. • Maintain technical documentation, runbooks, and architectural decision records, contributing to team knowledge sharing and operational readiness across on-call and incident response scenarios. • Apply CI/CD best practices to data pipeline development, including version control, automated testing, and deployment tooling to ensure reliable and repeatable pipeline delivery.
Job Requirements
- 4+ years of data engineering experience.
- At least 2 years of experience with Databricks or the Apache Spark ecosystem across Azure and/or AWS.
- Proficiency in PySpark, SQL, and Python with a strong track record of building and operating production-grade pipelines under SLA constraints.
- Hands-on experience with Delta Lake, including schema evolution, ACID transactions, optimize/vacuum lifecycle, and both incremental and streaming processing patterns.
- Hands-on experience with pipeline performance tuning and compute optimization in production Databricks environments.
- Solid working knowledge of PostgreSQL, including query optimization, schema design, and use as a source or sink in production data pipelines.
- Experience supporting and maintaining legacy ETL tooling (SSIS, Informatica, custom Python/SQL pipelines, or similar) in production.
- Experience supporting large-scale multi-tenant architectures with a focus on tenant isolation, per-tenant performance, and data privacy, including navigating tools and platforms that default to single-tenant assumptions.
- Proven ability to work collaboratively across data science, product, and infrastructure teams, owning end-to-end delivery in a cross-functional environment.
- Strong understanding of data governance, security, and compliance principles, including access control, data privacy, and protection of sensitive enterprise data across multi-tenant environments.
- Preferred Qualifications / Experience:**
- Experience operating Databricks workspaces across both Azure and AWS, including cost governance, cluster management, and cross-cloud data access.
- Experience optimizing Databricks workloads in a Serverless environment, including compute cost governance and performance tuning for serverless compute.
- Experience with Microsoft SQL Server in a data engineering or ETL context.
- Exposure to ML feature engineering or feature stores (Databricks Feature Store, Feast, or similar) supporting predictive analytics.
- Experience with customer onboarding automation or Infrastructure as Code (IaC) patterns for provisioning tenant data pipelines at scale.
- Databricks Certified Data Engineer Associate or Professional certification.
Related Guides
Related Categories
Related Job Pages
More Data Engineer Jobs
Role Description - Entwicklung, Betrieb und kontinuierliche Weiterentwicklung moderner Data-Warehouse-Lösungen - Konzeption, Implementierung und Optimierung von skalierbaren Datenpipelines und zentralen Datenflüssen - Sicherstellung eines stabilen, performanten und qualitativ hochwertigen Datenbetriebs - Analyse komplexer Geschäftsanforderungen und Entwicklung datenbasierter Lösungen für unterschiedliche Fachbereiche - Modellierung und Integration von Daten aus verschiedenen Quellsystemen - Optimierung bestehender ETL-/ELT-Prozesse hinsichtlich Performance, Wartbarkeit und Datenqualität - Mitarbeit bei der Modernisierung von Datenplattformen sowie der Migration bestehender Datenlösungen in Cloud-Umgebungen - Enge Zusammenarbeit mit Fachbereichen, Data Analysts und weiteren Stakeholdern zur Umsetzung neuer Datenanforderungen - Unterstützung bei der kontinuierlichen Weiterentwicklung der Datenarchitektur und der technischen Standards Qualifications - Mehrjährige Erfahrung als Data Engineer mit Fokus auf Data Warehouse - Fundierte Erfahrung im Aufbau, der Weiterentwicklung und dem Betrieb von Data-Warehouse-Lösungen - Sehr gute Kenntnisse in SQL sowie in der Entwicklung und Optimierung von ETL-/ELT-Prozessen - Erfahrung in der Datenmodellierung, beispielsweise nach Data Vault - Erfahrung mit Cloud-basierten Datenplattformen, idealerweise im Microsoft Azure Umfeld - Kenntnisse in Azure Databricks oder vergleichbaren modernen Data-Engineering-Plattformen - Analytische Denkweise sowie die Fähigkeit, komplexe Geschäftsanforderungen in nachhaltige Datenlösungen zu übersetzen - Erfahrung bei der Modernisierung von Datenlandschaften und der Migration von Legacy-Systemen ist ein Plus - Selbstständige, strukturierte und lösungsorientierte Arbeitsweise - Kommunikationsstärke sowie Freude an der Zusammenarbeit mit interdisziplinären Teams - Hohe Eigeninitiative und Verantwortungsbewusstsein - Fliessend in Deutsch und Englisch Company Description Die Coopers Group AG ist eine agile Schweizer Recruiting Agentur, die Spezialisten und Führungskräfte in den Bereichen IT, Life Sciences, Engineering und Finance vermittelt. Mit flexiblen Ansätzen bringen wir Kandidat:innen und Unternehmen zusammen, die nicht nur fachlich, sondern auch menschlich zusammenpassen.
Associate Director, Data Engineering
S4 Capital Groupa new age/new era digital advertising and marketing services company
• Design, build, and maintain scalable, reliable, and automated data pipelines using SQL, Python, and Databricks to support enterprise analytics. • Architect and optimize robust data models and infrastructure to ensure high data quality, integrity, and accessibility across the client's ecosystem. • Partner closely with the Data Science team to operationalize their work, deploying statistical and machine learning models into production environments using DataOps best practices. • Identify, design, and implement internal process improvements, including automating manual data processes and optimizing data delivery for scalability. • Collaborate with cross-functional teams to identify business problems, gather requirements, identify data sources, and provide data-driven solutions.
Data Engineering Intern, Fall 2026
Hone HealthHone is the premier men’s optimization clinic that helps men get their spark back and be their best self.
• Design, build, and maintain scalable data pipelines and ETL processes using Microsoft Fabric (Notebooks, Pipelines, Dataflows) to support analytics, reporting, and product use cases. • Integrate data from multiple internal and external sources, ensuring quality, consistency, and reliability across the medallion architecture. • Develop and maintain data models and transformations using dbt, contributing to bronze, silver, and gold layer modeling in the Fabric lakehouse. • Collaborate with engineers, analysts, and product teams to translate business requirements into technical data solutions — communicating through Slack and tracking work in Azure DevOps (ADO). • Participate in data quality checks, testing, validation, and performance optimization across pipeline and model layers. • Monitor, optimize, and troubleshoot data infrastructure for performance and scalability in a cloud-native Azure environment. • Follow engineering best practices around version control and CI/CD using GitHub, including branch management, pull requests, and code review. • Contribute to data documentation and ensure best practices around data governance, reliability, and scalability. • Contribute to the continuous improvement of data engineering processes and tools.
Contract Data Engineer
Hone HealthHone is the premier men’s optimization clinic that helps men get their spark back and be their best self.
• Design and build medallion architecture in dbt and Microsoft Fabric to enhance data analytics capabilities. • Create and maintain data ingestion pipelines to ensure efficient data flow and integration. • Establish data governance protocols, ensuring compliance with industry standards and best practices. • Implement data lineage and documentation to facilitate data traceability and transparency. • Develop and enforce data quality checks to maintain the integrity and accuracy of data assets. • Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business needs.
