Data Engineer – Flutter Functions

Betfair Romania Development

Data Engineer supporting procurement data pipelines and analytics at Flutter Entertainment in Cluj-Napoca. Collaborating across teams to ensure quality data products and governance.

Posted 6/29/2026full-timeCluj-Napoca • 🇷🇴 RomaniaJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering and management, with a strong focus on SQL proficiency, data quality controls, and pipeline orchestration. Capable of executing product roadmaps, maintaining data integrity, and collaborating effectively across teams to drive continuous improvement.

Highest-signal resume keywords

SQL ProficiencyData Quality ControlsPipeline OrchestrationDatabricks ExposureDimensional Modelling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLData Quality FrameworkDimensional ModellingELTETLPipeline OrchestrationData CatalogData LineageRBACKPI Definitions

Soft Skills

Structured Problem SolvingDocumentation DisciplineCollaborative Working StyleContinuous Improvement MindsetCuriosity and Openness

Tools & Technologies

DatabricksSnowflakeBigQueryAirflowAzure Data FactoryDbtPower BITableau

Certifications & Qualifications

Bachelor's Degree in Relevant Field

Industry Keywords

Data EngineeringData ManagementProcurement DataFinance ReconciliationP2PSourcing

Tech Stack

Tools & technologies

AirflowAzureBigQueryETLPythonSQLTableau

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

Solid foundation in platform operations, with exposure to monitoring, incident response and performance tuning, ideally on Databricks.
Working knowledge of dimensional modelling, ELT or ETL patterns, and pipeline orchestration.
Proficiency in SQL and a modern data platform.
Able to read code, specs and data models and contribute clearly to reviews.
Hands-on experience applying data quality controls, catalog and lineage practices, and RBAC under an established framework.
Structured problem solving, documentation discipline, and a continuous improvement mindset.
Collaborative working style, comfortable taking direction and asking clarifying questions early.
Bachelor's Degree in a relevant field or equivalent practical experience.
2 to 4 years in data engineering or data management, with hands-on contribution to production data pipelines.
Hands-on experience with SQL and at least one analytics platform such as Databricks, Snowflake or BigQuery.
Python is a plus.
Exposure to Databricks is strongly preferred.
Willingness to deepen Databricks capability rapidly is essential.
Exposure to orchestration and transformation tooling such as Airflow or Azure Data Factory and dbt.
Exposure to BI tools such as Power BI or Tableau and building or consuming certified datasets.
Familiarity with procurement, finance or other enterprise data structures (P2P, sourcing, finance reconciliation) is a plus.
Demonstrating curiosity and openness toward AI and emerging technologies, with a willingness to continuously learn, adapt, and share knowledge.
Demonstrated ability to work effectively with diverse teams across various departments, fostering an environment of open communication and shared goals to achieve collective success.
Demonstrates a strong focus on achieving high-quality outcomes, consistently pushing for greater efficiency and performance.

Benefits

Comp & perks

€1,000 per year for self-development
Company share scheme
25 days of annual leave per year
20 days per year to work abroad
5 personal days/year
Flexible benefits: travel, sports, hobbies
Extended health, dental and travel insurances
Customized well-being programmes
Career growth sessions
Thousands of online courses through Udemy
A variety of engaging office events