Role Description - Data platform engineering: Design and maintain scalable batch and near-real-time data pipelines across mobile applications, NFC/fuel transactions, station integrations, ERP integrations, payments, support systems, and operational databases. - Data modeling: Create clean, reusable data models for core entities such as customers, vehicles, drivers, stations, transactions, wallets, limits, invoices, products, maintenance services, and geographic coverage. - Reliability and quality: Implement data validation, lineage, observability, alerting, reconciliation, and automated quality checks to ensure business-critical dashboards and reports are accurate and timely. - Analytics enablement: Partner with analytics, product, finance, operations, and customer success teams to deliver self-service datasets, metrics layers, and well-documented data marts. - Performance and cost optimization: Tune queries, storage layouts, orchestration schedules, and cloud resources to improve platform performance and manage infrastructure cost. - Data governance and security: Apply data access controls, PII handling, retention practices, auditability, and compliance-aware engineering patterns across the data lifecycle. - Integration engineering: Build robust ingestion patterns for APIs, webhooks, CDC, files, event streams, third-party integrations, and partner station data feeds. - DevOps for data: Use CI/CD, version control, automated testing, infrastructure-as-code, and deployment standards for data pipelines and transformations. - Incident management: Troubleshoot data incidents, conduct root-cause analysis, reduce recurring failures, and communicate impact clearly to stakeholders. - Technical mentorship: Review designs and code, establish engineering standards, mentor junior team members, and raise the quality bar for data engineering at PetroApp. Qualifications - 5+ years of professional experience in data engineering, analytics engineering, platform engineering, or backend engineering with strong data ownership. - Advanced SQL skills, including query optimization, data modeling, window functions, incremental transformations, and large-table performance tuning. - Strong Python programming experience for data pipelines, automation, testing, and production-grade data workflows. - Hands-on experience with workflow orchestration such as Airflow, Dagster, Prefect, or similar tools. - Experience with modern data warehouses or lakehouse platforms such as BigQuery, Snowflake, Redshift, Databricks, Delta Lake, Iceberg, or equivalent. - Experience building reliable ELT/ETL pipelines using tools such as dbt, Spark, Kafka, Flink, Fivetran, Stitch, custom API ingestion, or CDC frameworks. - Practical understanding of data quality, schema evolution, monitoring, alerting, backfills, idempotency, and failure recovery. - Experience designing dimensional, wide-table, and event-based data models for BI, analytics, and operational reporting. - Comfort working with cloud platforms such as AWS, GCP, or Azure, plus Git-based engineering workflows. - Strong communication skills with the ability to translate business requirements into clear technical designs and delivery plans. Requirements - Experience in fintech, payments, fleet management, logistics, mobility, marketplace, fuel, or high-volume transaction platforms. - Knowledge of event-driven architectures, streaming data, CDC, API integrations, data contracts, and data mesh or domain-oriented data ownership. - Experience supporting BI tools such as Power BI, Looker, Tableau, Metabase, Superset, or similar platforms. - Familiarity with MLOps or feature engineering for fraud detection, anomaly detection, forecasting, customer segmentation, or optimization use cases. - Experience with data privacy, access control, encryption, secrets management, and compliance expectations in the Middle East or multi-country operations. Core Technical Stack Expectations - Languages: SQL, Python; optional Scala or Java for distributed processing. - Transformation and modeling: dbt or equivalent; dimensional modeling; metrics layers. - Orchestration: Airflow, Dagster, Prefect, or similar. - Storage and compute: cloud warehouse, data lake/lakehouse, object storage, distributed processing. - Streaming and integration: Kafka or equivalent, CDC, APIs, webhooks, files, partner data feeds. - Engineering practices: Git, CI/CD, automated tests, Docker, Kubernetes or containerized deployment, Terraform or infrastructure-as-code. - Observability: data quality checks, lineage, pipeline monitoring, logs, alerts, runbooks, and service-level objectives for data products. Benefits - Competitive salary and benefits package. - Opportunity to work on cutting-edge technology with a passionate team. - Career growth and development opportunities. - A collaborative and inclusive work environment.

**What You Will Do ❓** - Design, build, and maintain scalable batch and real-time data pipelines using Maxwell, Kafka, Spark, and dbt to power analytics and business-critical applications. - Develop and optimize data models following Medallion Architecture (Bronze, Silver, Gold) to create reliable, reusable, and high-quality datasets. - Build and maintain cloud-native data platforms using S3, Spark, Trino, and BigQuery, ensuring scalability, reliability, and cost efficiency. - Design robust data ingestion frameworks leveraging CDC (Maxwell), Kafka, and event-driven architectures to support near real-time data processing. - Create, optimize, and maintain data warehouses and data marts that enable fast, reliable reporting and self-service analytics. - Partner closely with Product Managers, Data Analysts, Backend Engineers, and Business stakeholders to translate business requirements into scalable data solutions. - Develop reusable dbt models, testing frameworks, and documentation to improve data quality, governance, and developer productivity. - Optimize Spark jobs, Trino queries, and storage layouts for performance, reliability, and cost efficiency. - Own the end-to-end lifecycle of critical data pipelines, ensuring high availability, monitoring, SLA adherence, and proactive incident resolution. - Build and enhance the core data platform by developing reusable frameworks, automation, CI/CD pipelines, and engineering best practices. - Ensure data quality through validation, monitoring, lineage, and observability while implementing best practices for security and governance. - Enable analytics teams by delivering trusted datasets, semantic models, and dashboards that power decision-making through Metabase.

Role Description We're looking for a Finance Engineer — someone who can turn manual finance and accounting processes into scalable, automated, AI-supported workflows. This role sits at the intersection of Finance, Accounting, Systems, Automation, and AI. - Build and improve workflows for reporting, forecasting, month-end review, reconciliations, and financial controls. - Work directly with clients: understand their finance and accounting needs, configure tools, support vendor onboarding, and own system improvements end-to-end. - Translate finance and accounting needs into system logic, automations, workflows, and documentation. - Automate repetitive finance work using AI tools, low-code tools, integrations, and internal workflows. - Connect and structure data from accounting systems, CRMs, payment tools, spreadsheets, BI tools, and data warehouses. - Build checks, controls, and validation logic to improve accuracy and reduce manual errors. - Partner with our engineering team on APIs, integrations, data pipelines, and workflow orchestration. Qualifications - 5+ years of experience in finance systems, finance operations, automation, or engineering roles within complex multi-stakeholder or enterprise environments. - 1+ year of hands-on experience building AI-powered automations, agents, prompts, workflows, or internal tools (Claude / Claude Code, Cursor, Copilot, custom LLM builds, or similar). - Experience with APIs, system integrations, data warehouses, and automation tools. - Strong understanding of finance and accounting processes: month-end close, reconciliations, AP / procure-to-pay, revenue, reporting, and corporate finance. - Ability to understand how financial data flows between departments and systems. - Fluent English (C1+) and excellent client-facing communication skills — you'll work directly with customers' founders and finance teams. - Strong drive to eliminate repetitive manual work. - Proactivity and high level of responsibility. - Ability to work in a fast-paced environment. Requirements - Python or other scripting experience. - Experience administering financial, accounting, billing, or ERP systems. - Experience with tools like NetSuite, QuickBooks, Xero, Stripe, Salesforce, HubSpot, Zuora, BigQuery, Snowflake, PostgreSQL, Looker, Power BI, Tableau, Zapier, Make, n8n, or Workato. - Proven impact in numbers: hours saved, manual work reduced, faster reporting, or fewer errors. - Experience working with US-based clients or startups. Recruitment Process - Soft skills interview with the recruiter. - Hard skills interview with the Head of FP&A. - Test task. - Culture fit interview with the VP of Operations. Benefits - Build the future of finance work — design AI-native finance operations, not just maintain them. - Rapid skills improvement (you'll work with multiple client businesses with different models and challenges). - Growth opportunities according to our seniority grading (it comes with a compensation increase). - Flexible schedule and time-off policy. - 18 days of paid vacation per year, paid sick leaves.

Company Description We’re one of the world’s leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages. We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we’re breaking new ground in software innovation too, redefining what’s possible for our global worldwide. Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak. Job Description As a Data Engineer, you will play a key role in creating, migrating, and maintaining regulatory reporting systems on Google Cloud Platform (GCP). The Regulatory Data team is a crucial function of the Data Engineering department, responsible for building and maintaining near real-time and batch reporting systems to fulfil regulatory requirements. The team utilises complex Business logic to transform internal data models into those required by industry regulators and third parties. Using your passion for delivering innovative solutions you will support our continued migration from on-premise SQL Server systems to GCP as the team creates new GCP reporting systems You will support this migration while also developing new cloud-native solutions and exploring AI-driven development and automation to improve efficiency, consistency and reliability across the team's processes. Qualifications - Experience with Google BigQuery. - SQL development experience, with the ability to write complex queries, stored procedures, and performance-tune data-intensive workloads. - Familiarity with GCP services such as Cloud Storage, Cloud Functions, Pub/Sub, or Cloud Composer. - Experience with data pipeline development (ETL/ELT) and orchestration tooling. - Exposure to Infrastructure as Code such as Terraform, and CI/CD pipelines such as Git, GitLab. - Methodical, with high attention to detail and the ability to break down complex requirements into simple solutions. - Interest in AI-assisted development tooling, such as Claude Code. - Ability to work to deadlines in a fast-paced, reactive environment. - SQL Server experience to support legacy systems during migration. Additional Information - Developing and maintaining regulatory data submission systems, both existing on-premise and new cloud-based solutions in GCP/BigQuery. - Building and maintaining automated data pipelines for ingestion, transformation, and loading of regulatory data. - Supporting the migration of legacy SQL Server solutions to BigQuery, working closely with seniors and technical leads on architecture and data modelling. - Implementing data validation, monitoring, and alerting to ensure accuracy, consistency, and reliability of regulatory submissions. - Leveraging AI tooling, such as Claude Code, and contributing to the team's automation strategies to reduce manual effort and improve quality. - Participating in code reviews and adhere to departmental standards and the development process. - Conducting QA to ensure solutions are accurate, efficient, and performant. - Creating and maintaining relevant documentation. - Collaborating with other team members to deliver high-quality solutions within required timeframes. By applying to us you are agreeing to share your Personal Data in accordance with our Recruitment Privacy Notice - https://www.bet365careers.com/privacy-policy At bet365, we're committed to creating an environment where everyone feels welcome, respected and valued. Where all individuals can grow and develop, regardless of their background. We're Never Ordinary, and we're always striving to be better. If you need any adjustments or accommodations to the recruitment process, at either application or interview, please don’t hesitate to reach out.