Data Engineer

• Own the data architecture across OneOcean's data organisation — operational, lakehouse, analytical-serving and vector layers — providing a coherent target state and a pragmatic path to it.
• Lead the discovery, documentation and specification of the data structures and models required to support product and analytics roadmaps.
• Reverse-engineer source data from OneOcean SaaS products — building accurate logical models of upstream systems and identifying the data contracts, grain and semantics our pipelines depend on.
• Design the right data store for each use case — choosing between OLTP, columnar / OLAP, lakehouse and vector approaches; making the trade-offs explicit.
• Define and maintain conceptual, logical and physical data models; produce clear ERDs, lineage and dimensional designs (star / snowflake, conformed dimensions, surrogate keys).
• Establish and enforce modelling standards, naming conventions, data contracts and schema-evolution practices across teams.
• Partner with the Data Team Lead, BI Team Lead and AI Team Lead — translating product and analytics needs into specifications their engineers can build from, and unblocking architectural decisions as they arise.
• Collaborate with Product, Architecture and Engineering Team Leads to align data direction with the wider engineering strategy.
• Champion data governance — cataloguing, lineage, ownership, quality, security and privacy.
• Document architectural decisions (ADRs) so the why is preserved alongside the what.
• Mentor engineers across the data organisation on modelling, design and architectural reasoning — without line-managing them.
• Stay current with the data landscape and bring in proven techniques as they mature; foster a culture of continuous improvement, innovation and knowledge sharing.

Data Architect

• Design, build, and operate a secure, scalable, AI‑ready data and analytics platform on Microsoft Azure and Microsoft Fabric, including OneLake, Lakehouse, and Warehouse components.
• Administer and optimize Azure and Fabric platform resources including subscriptions, resource groups, RBAC, Azure Policies, and Fabric capacities (F SKUs), workspaces, and item governance.
• Manage storage and compute layers across the platform covering ADLS Gen2, Delta Lake, Lakehouse/Warehouse, SQL pools, and Spark runtime and capacity settings.
• Enable and operate data ingestion and transformation services using Azure Data Factory, Synapse Pipelines, Fabric Data Factory, and Dataflows Gen2, focusing on platform configuration, reliability, and standards (no pipeline business logic).
• Establish platform reliability and operational excellence including monitoring, alerting, autoscaling, performance tuning, cost control, tagging, chargeback/showback, and capacity optimization.
• Harden platform security end to end leveraging Entra ID (Azure AD), PIM, conditional access, managed identities, Key Vault, private endpoints, encryption, and network isolation.
• Implement governance, compliance, and data protection controls using Microsoft Purview (catalog, lineage, classification), DLP, sensitivity labels, retention policies, and auditing.
• Enable AI/ML and advanced analytics workloads by integrating Azure Machine Learning and Fabric ML experiences, including feature stores, registries, compute access, and inference endpoints from a platform perspective.
• Oversee CI/CD and lifecycle management for analytics and data platform artifacts including Fabric Git integration, Azure Repos/GitHub, branching strategies, automated deployments, and environment promotion.
• Act as tenant and workspace administrator and platform enabler for Fabric and Power BI (capacity settings, gateways, semantic models, refresh, RLS/OLS), while collaborating cross‑functionally, defining best practices, and coaching teams on platform usage.

Data Platform Administrator

• Conduct 60-minute technical interviews for Senior Data Engineer candidates.
• Evaluate candidates' hands-on experience across modern data platforms and cloud-based data architectures.
• Assess technical depth, engineering best practices, problem-solving ability, and real-world project experience.
• Explore candidates' previous projects through detailed technical discussions and follow-up questions.
• Evaluate knowledge of data engineering principles, cloud architecture, scalability, security, governance, and performance optimization.
• Assess candidates' understanding of data lakes, lakehouses, data warehouses, and modern analytics platforms.
• Assess communication skills and the ability to explain complex technical concepts clearly.
• Complete structured interview scorecards and provide hiring recommendations after each interview.
• Collaborate with recruiters to ensure consistent evaluation standards.
• Contribute to improving interview questions and technical assessment processes when needed.

Senior Data Engineer, Interviewer

• Execute the product roadmap and backlog.
• Translate epics into technical work packages and sprint plans.
• Capture technical impacts of business requirements and provide effort and risk estimates.
• Feedback recommendations for prioritisation.
• Participate in UAT for data layers and prepare evidence for release sign off by the manager.
• Maintain regression tests for shared datasets.
• Apply QA and continuous improvement practices for data products and pipelines.
• Build and publish certified datasets and contribute to a consistent semantic layer for BI tools.
• Implement KPI definitions and metric calculations as agreed with the Insights team.
• Protect one source of truth.
• Build standard executive and operational dashboards from defined specifications, translating complex data into clear visual outputs.
• Tune performance for shared datasets that power dashboards and scheduled reports.
• Operate the dataset certification and change control process under the manager’s direction, with clear communication of impacts.
• Build and maintain ingestion, transformation and orchestration of procurement data pipelines.
• Align schedules and dependencies with source systems.
• Apply data contracts with sources and consumers.
• Implement schema changes, versioning and backward compatibility under guidance.
• Operate monitoring, alerting and incident response.
• Maintain runbooks and contribute to reducing MTTR and tracking pipeline success rate.
• Support capacity, performance and platform cost management through tuning and right sizing.
• Support master and reference data processes.
• Execute lifecycle management for raw, curated and mart layers in line with the defined strategy.
• Apply data policies, standards and naming conventions.
• Keep documentation current and audit ready.
• Implement the data quality framework and SLAs.
• Apply rules, monitor results and progress remediation through the controlled workflow.
• Apply privacy, access control and retention in line with legal and InfoSec guidance.
• Support role-based access reviews.
• Maintain the data catalog, lineage and business glossary entries to support self-service discovery.
• Contribute to model design for core domains such as suppliers, spend, contracts, POs, invoices and savings, under the manager's direction.
• Execute backup, recovery and resilience procedures to ensure availability targets are met.

Data Engineer – Flutter Functions

• Hands-on development and optimization of the data backend, ensuring stability, performance, and architectural consistency
• Build and optimize Snowflake data models and workloads (raw → curated → data products), with strong focus on performance and cost efficiency
• Develop and maintain transformation logic in dbt (modeling, refactoring, tests, documentation, macros) to ensure data quality and scalability
• Orchestrate reliable data pipelines using Airflow/Astronomer (DAG design, dependencies, retries, monitoring/alerting) for production readiness
• Use Git + CI/CD to enforce code quality and enable automated testing and deployments across the data platform
• Apply AI-assisted development tools in day-to-day work to boost productivity, improve code quality, and maintain high-quality documentation, contributing to robust and maintainable solutions
• Work with IT and business colleagues to develop solutions to specific problems that at times leverage existing solutions and systems
• Build professional relationships with clients, management, and team members to ensure the delivery of proposed solutions

Snowflake Data Engineer

• Design, build and maintain robust data pipelines (ETL/ELT) for structured and unstructured data
• Develop and operate data solutions in the Microsoft Azure environment, using Databricks and/or Microsoft Fabric
• Use Python and SQL (and frameworks such as PySpark) for data processing, transformation and automation
• Contribute to data integration, data modeling, data quality and data provisioning across projects
• Work with modern data architecture concepts such as Lakehouse and Medallion architectures
• Collaborate with colleagues and clients to translate requirements into clean, maintainable technical solutions

• Delivering End to End IT Consulting Services - From Team Augmentation and Dedicated Teams to Custom Software Development
• Deliver scalable enterprise systems, intelligent automation frameworks, and digital transformation platforms
• Sustain global players in BSFI (Banking, financial services and insurance), Telecom, Retail & E-commerce, Energy and Utilities, Automotive, Manufacturing, Logistics, High Tech
• Collaborate within an international team of 500+ software engineers
• Work on projects ranging from large-scale enterprises to startups

• **What you will do:**
• - Oversee the delivery of data and content migration projects, data governance, and data quality solutions;
• - Collaborate with clients and the fme delivery team on data-related initiatives to ensure project success;
• - Review existing migration tools and recommend improvements to enhance performance;
• - Develop and implement action plans to provide timely technical solutions for critical customer needs;
• - Stay current with new testing tools and strategies;
• - Act as a Subject Matter Expert (SME) for content migration solutions, supporting multiple projects simultaneously;
• - Lead migration projects, identify risks or issues early, and escalate them when needed.

Senior Data Migration Engineer – ETL

• Be an effective team player of a Scrum Team - understanding and contributing to the agile delivery process and taking ownership of your team's processes.
• To promote the production of reusable code and modules where appropriate with a view to maximizing effort and reducing development costs applying principles of Agile delivery.
• To ensure risks and issues are identified in a timely manner and effectively communicated with proposed resolution and mitigation strategies to the Data Delivery Manager.
• Work as an effective member of a scrum team - understanding and contributing to the agile delivery process, and taking ownership for your team's software quality from concept to production.
• Write and maintain functional and technical specifications.
• Monitor, optimize and troubleshoot database, microservice, stream and ML service performance.
• Analyse code for problem resolution.
• Thorough, demonstrable unit testing.

Data Engineer – Flutter

• Design and implement scalable, maintainable, and secure batch & streaming data pipelines and architectures that support enterprise-wide data needs
• Define standards for data engineering, data product design, and pipeline orchestration using modern tools and cloud-native technologies
• Establish and enforce engineering best practices around code quality, testing, documentation, and deployment
• Contribute to the evolution of the data platform, ensuring systems are modular, interoperable, and resilient
• Lead technical design and code reviews, mentoring peers and raising the bar for engineering excellence
• Partner with other data engineering teams, analytics, and data science to deliver reusable data assets and shared infrastructure
• Identify and resolve architectural bottlenecks in the current data platform and propose improvements that reduce complexity and boost performance
• Act as a technical liaison between engineering, product, and analytics teams, ensuring alignment on architecture and data strategy
• Provide technical leadership and guidance to other data engineers and contribute to the team’s overall growth and maturity
• Help evaluate and onboard new technologies, frameworks, and practices to keep our stack modern and efficient
• Design, develop, and maintain scalable ETL/ELT pipelines to support data products, analytics, and operational systems
• Work with large-scale, complex datasets and ensure data is clean, well-modelled, and accessible across the organization
• Develop and maintain batch and streaming data pipelines and data platforms using modern tools and technologies

Principal Data Engineer

• Be ready to work with Architects and Technical Leads in order to perform system & gap analysis with given business specifications and define functional and non-functional requirements for the software components, where SDLC and best-practices are self-implied.
• Be involved in researching, producing POCs and evaluating new methodologies & technologies that improve quality, reliability, scalability, security, and performance of Flutter Studios Technology.
• Deliver projects within agreed deadlines with a high degree of confidence and quality while taking responsibility for the delivered products.
• Prove to be an effective team player in a Scrum Team while understanding and contributing to the agile delivery process and following the team’s ways of working.
• Design and implement low-latency, high-availability and performant applications.
• Participate in the software development process from the analysis phase to release, including: design, document, test and develop solutions by emphasizing code review & peer design activities.
• Write reusable, testable, and efficient code while also inspiring other data engineers to do so.
• Implement and integrate data storage solutions.
• Be proactive in the identification of opportunities to improve and rationalise applications and processes across the whole Data team, working in close collaboration with other Data team members and subject matter experts.
• Ensure that accurate and effective support documentation is maintained to reflect code development and changes.
• Be responsible for effectively escalating any risks & issues identified in a timely manner to the Data Delivery Manager while also providing resolution and mitigation strategies.

Data Engineer jobs in Romania

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Data Architect

Data Platform Administrator

Senior Data Engineer, Interviewer

Data Engineer – Flutter Functions

Snowflake Data Engineer

Data Engineer

Data Engineer

Senior Data Migration Engineer – ETL

Data Engineer – Flutter

Principal Data Engineer

Senior Data Engineer