The Wow

This role will design and implement the automation of our data platform. The focus will be on enabling and optimizing the data lifecycle by applying DevOps practices, such as Infrastructure as Code (IaC), CI/CD, and GitOps, to ensure the efficiency, reliability, and speed of our data deliveries.

A taster of what you will be involved with: 

• Develop and maintain the data platform's infrastructure using Terraform.
• Implement and manage CI/CD pipelines for the automation of data and ai processes and pipelines.
• Automate the provisioning, configuration, and monitoring of resources in AWS.
• Apply GitOpsprinciples to manage configurations and deployments.
• Ensure the security, scalability, and resilience of the infrastructure through automation.
• Collaborate with Data Engineers to optimize the data development lifecycle (DDLC).
• Own the automation and infrastructure of orchestration tools like Airflow.
• Document the automation architecture and deployment processes.
  
  

Must haves:

• Solid experience with Infrastructure as Code (IaC) tools, especially Terraform.
• Experience in creating and managing CI/CD pipelines (e.g., Github Action, AWS CodePipeline).
• Deep knowledge of version control tools and workflows with GIT.
• Experience in automation scripting with Python, AWS CLI, Spark.
• Knowledge of AWS services automation and management.|
  
  

Nice to haves:

• Familiarity with the AWS data ecosystem (S3, Glue, Lambda, Redshift, Snowflake).
• Familiarity with orchestrators like Airflow.
• Familiarity with data streaming technologies such as Kafka.
• Knowledge of monitoring and visualization tools (Prometheus, Grafana, CloudWatch).
• Basic knowledge of containerization (Docker, Kubernetes).
• Excellent verbal and written English communication skills.

What we are looking for

• University Degree in Computer Science, Engineering or equivalent
• At least 2 years of experience in DataOps, DevOps, or infrastructure automation
• Excellent verbal and writing English communication skills
• Good learning mindset
• Able to set priorities and multitask

What we offer

Much like riding a rollercoaster, sometimes life at Betsson can be lightning fast with twists and turns but always FUN! Then again, what else would you expect from a business 75% millennial and 1700 strong, spread across 7 offices with 900 based out of our Malta HQ alone! We recognise it may not be for the faint-hearted, but if you’re a go-getter, initiator and adrenaline junkie, always striving to push the boundaries and challenge yourself, then you’ll fit right in.

Challenge accepted?

By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

The Wow

This role will contribute in designing and developing our platform to fulfil the business needs and to also improve our systems. Within this capacity you will have the chance to design new data pipelines, maintain platforms hosted on data streams for batch and real-time loading and real-time visualisations.

A taster of what you will be involved with: 

• Maintaining and evolving our existing data platform;
• Building processes to ingest data from Kafka, APIs and Databases using AWS MSK Connect.
• Development and Maintenance of real-time data processing applications using frameworks like Spark Structured Streaming and Kafka Streams.
• Applying transformations to data streams;
• Being involved in data modelling following standards e.g. Inmon, Kimball, Data Vault;
• Ensuring data quality by verifying data consistency and accuracy;
• Keeping up to date on research and development of new technologies and techniques to enhance our data platform;
• Have an investigative mindset to be able to troubleshoot – thinking outside the box when it comes to troubleshooting problems and incident management;
• Full ownership on projects and tasks assigned together with being able to work within a Team;
• Able to document well processes and perform knowledge sharing sessions

What we are looking for:

Must haves: 

• Experience with modern cloud database technologies such as Snowflake;
• Experience with orchestrating data pipelines using Airflow;
• Experience with AWS Glue;
• Experience with Apache Iceberg;
• Experience with SQL, and Data Integration Tools
• Experience with any programming language like Python or Scala;
• Knowledge on AWS Services like S3/Lambda/API Gateways/DMS/RDS;
• Development experience in both Microsoft, and Linux/Cloud environments;
• Have strong analytical and problem-solving skills

Nice to have:

• Familiar with Data Warehousing concepts and data modelling techniques such as Inmon, Kimball, Data Vault;
• Familiar with AWS Services such as MSK and EMR;
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with Time-series or Analytics Databases such as Elasticsearch;
• Familiar with data streaming using technologies such as Kafka;
• Familiar with software versioning tools like GIT;
• Familiar with infrastructure scripting like Terraform;
• Familiar with Data Monitoring and Visualisation tools such as Prometheus and Grafana, Cloudwatch;
• Scripting – Powershell, Unix Scripting;
• At least 2 years experience in Data Engineering;
• Excellent verbal and writing English communication skills;
• Good learning mindset;
• Able to set priorities and multitask

What we offer

• Fitness-wellness allowance  🧗‍♂️
• Company mobile phone for private use with 100 GB  📱
• Annual HUF devaluation compensation  💡
• Hybrid model: 3 days in the office 🏢  & 2 days from home  🏠
• Private Health Insurance  🩺
• Career development  📈
• Technical and soft-skill training opportunities 🎓
• Breakfast, fruits & lunch 🍎
• Team building events  🥳

Challenge accepted?

If you are interested to learn more, please apply with your CV in English.

By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

The Wow

This role will contribute in designing and developing our platform to fulfil the business needs and to also improve our systems. Within this capacity you will have the chance to design new data pipelines, maintain platforms hosted on data streams for batch and real-time loading and real-time visualisations.

A taster of what you will be involved with: 

• Maintaining and evolving our existing data platform;
• Building processes to ingest data from Kafka, APIs and Databases using AWS MSK Connect.
• Development and Maintenance of real-time data processing applications using frameworks like Spark Structured Streaming and Kafka Streams.
• Applying transformations to data streams;
• Being involved in data modelling following standards e.g. Inmon, Kimball, Data Vault;
• Ensuring data quality by verifying data consistency and accuracy;
• Keeping up to date on research and development of new technologies and techniques to enhance our data platform;
• Have an investigative mindset to be able to troubleshoot – thinking outside the box when it comes to troubleshooting problems and incident management;
• Full ownership on projects and tasks assigned together with being able to work within a Team;
• Able to document well processes and perform knowledge sharing sessions

What we are looking for:

Must haves: 

• Experience with modern cloud database technologies such as Snowflake;
• Experience with orchestrating data pipelines using Airflow;
• Experience with AWS Glue;
• Experience with Apache Iceberg;
• Experience with SQL, and Data Integration Tools
• Experience with any programming language like Python or Scala;
• Knowledge on AWS Services like S3/Lambda/API Gateways/DMS/RDS;
• Development experience in both Microsoft, and Linux/Cloud environments;
• Have strong analytical and problem-solving skills

Nice to have:

• Familiar with Data Warehousing concepts and data modelling techniques such as Inmon, Kimball, Data Vault;
• Familiar with AWS Services such as MSK and EMR;
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with Time-series or Analytics Databases such as Elasticsearch;
• Familiar with data streaming using technologies such as Kafka;
• Familiar with software versioning tools like GIT;
• Familiar with infrastructure scripting like Terraform;
• Familiar with Data Monitoring and Visualisation tools such as Prometheus and Grafana, Cloudwatch;
• Scripting – Powershell, Unix Scripting;
• At least 2 years experience in Data Engineering;
• Excellent verbal and writing English communication skills;
• Good learning mindset;
• Able to set priorities and multitask

What we offer

Much like riding a rollercoaster, sometimes life at Betsson can be lightning fast with twists and turns but always FUN! Then again, what else would you expect from a business 75% millennial and 1700 strong, spread across 7 offices with 900 based out of our Malta HQ alone! We recognise it may not be for the faint-hearted, but if you’re a go-getter, initiator and adrenaline junkie, always striving to push the boundaries and challenge yourself, then you’ll fit right in.

Challenge accepted?

By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

The Wow

We are seeking a motivated and detail-oriented Data Operations Engineer to join our team. The ideal candidate will act as the first line of defense in our data operations, providing essential support that ensures optimal data quality and reliability. This role involves active monitoring, incident resolution, and engagement with data requests while continuously improving our data processes and systems.

A taster of what you will be involved with: 

• Provide First Line Support for data-related incidents, actively monitoring systems for anomalies, and quickly addressing issues as they arise.
• Perform rigorous investigations into data quality, identifying discrepancies, and implementing corrective actions in collaboration with other teams.
• Handle incoming data requests from various stakeholders, ensuring timely and accurate delivery of information.
• Collaborate on data engineering initiatives, focusing on the enhancement of existing processes and the development of new solutions to improve overall data workflow.
• Engage in incident monitoring and resolution, escalating more complex issues to second line support as necessary.
• Identify opportunities for process enhancements and implement improvements in data engineering tasks.
• Communicate clearly and effectively with team members and stakeholders to ensure a shared understanding of data expectations and outcomes.

What we are looking for:

• Preferably 2 years experience in a similar role
• Proficiency in SQL for querying and managing datasets
• Experience with scripting languages to automate and streamline tasks.
• Interest in leveraging AI to improve operational efficiency and automation.
• Familiarity with monitoring tools and incident resolution methodologies.
• Reliability and strong accountability in managing data operations and supporting team objectives.
• A proactive approach to problem-solving with strong attention to detail.
• Committed to maintaining high standards of data quality and integrity.
• Exposure to AI-powered tools (e.g. Copilot) in engineering / operational workflows.

Nice to have: 

• Experience with Apache Airflow (DAG development and monitoring)
• Experience with Apache NiFi
• Experience working with Apache Kafka
• Infrastructure-as-Code knowledge (e.g., Terraform)
• Data reporting experience with SSRS (SQL Server Reporting Services)
• Data visualization e.g. Qlik Sense, Power BI

What we offer

Much like riding a rollercoaster, sometimes life at Betsson can be lightning fast with twists and turns but always FUN! Then again, what else would you expect from a business 75% millennial and 1700 strong, spread across 7 offices with 900 based out of our Malta HQ alone! We recognise it may not be for the faint-hearted, but if you’re a go-getter, initiator and adrenaline junkie, always striving to push the boundaries and challenge yourself, then you’ll fit right in.

Challenge accepted?

By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

The Analytics Engineering Technical Lead will define and own the modeling architecture, standards, and technical direction within RSI’s cloud-native Data Platform. This role is accountable for ensuring that analytics-ready data is reliable, scalable, and aligned to long-term business needs across growth, operations, and risk.

You will lead the design and governance of core data models in Snowflake and dbt, establishing best practices that enable high-quality, self-service analytics without sacrificing trust or performance. As a hands-on technical leader, you will set standards for modeling, testing, documentation, and deployment while mentoring other Analytics Engineers and raising the overall technical bar of the team.

This role partners closely with Data Engineering, Analytics, and business stakeholders to translate evolving requirements into durable data products. You will help balance speed and governance, prioritize platform investments, and ensure our data foundation scales with the business.

Our modern data stack includes Snowflake, AWS, Python, Airflow, and dbt.

What You'll Do:

• Lead the design, development, and lifecycle management of curated datasets, dbt models, and analytics data marts aligned to business domains and metrics.
• Establish and evolve standards and best practices for dbt modeling, testing, documentation, and code organization to support long-term scalability.
• Ensure analytical datasets are accurate, reliable, and trusted, serving as a single source of truth for business, product, and stakeholders.
• Embed data quality checks, documentation, and governance directly into analytics pipelines.
• Partner closely with Product, Data Engineering and Analytics teams to translate business requirements into well-modeled, performant data products.
• Mentor and support Analytics Engineers through technical guidance, design reviews, and knowledge sharing.
• Continuously improve and modernize analytics workflows by introducing automation, tooling enhancements, and AI-assisted development where appropriate.
• This role includes technical leadership and mentoring responsibilities for the team, including other Analytics Engineers.

What You'll Bring:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related quantitative discipline.
• Technical Leadership: Proven experience defining technical direction, standards, and architectural decisions within analytics engineering or curation teams.
• Data Modeling Expertise: Deep understanding of dbt, data marts, dimensional modeling, and self-service BI enablement.
• Data Engineering Background: 7+ years of experience in data warehousing or development; 5+ years of experience in hands-on data engineering using SQL and Python.
• Cloud Infrastructure: Proficiency with cloud platforms (AWS, GCP, or Azure), including containerization (Docker/Kubernetes).
• Tooling & Orchestration: Experience with tools like dbt, Airflow, S3, REST APIs, and large-scale DWHs (Snowflake, Redshift, BigQuery, etc.).
• Change Management: Skilled at leading cross-functional data initiatives and driving adoption of new tools and standards.
• People Leadership: Experience mentoring and guiding distributed teams across time zones.
• Communication: Strong written and verbal English skills with the ability to collaborate across technical and business functions.
• Able to travel occasionally both domestically and internationally #LI-HYBRID

❗️IMPORTANT: This position is office based for our office in Birkirkara, Malta.

❗️We can provide relocation assistance if you're outside of the city or country.

The Senior Data Operations Engineer will support the management and optimisation of the company’s data systems and processes, reporting directly to the Data Operations Lead.

This role requires a technically proficient individual with strong analytical skills to ensure data integrity, accessibility, and security across the data platform. The ideal candidate will have hands-on experience in data management, a keen eye for detail, and the ability to work collaboratively with different stakeholders.

✅ Responsibilities:

Data Management and Maintenance

• Assist in developing and enforcing policies for effective data management.
• Ensure data accuracy, consistency, and security through regular maintenance and monitoring.
• Support the implementation of data quality standards and maintain data governance practices.

Operations Support

• Manage and optimise data pipelines and ETL processes to ensure smooth and efficient workflows.
• Troubleshoot and resolve data-related issues promptly to minimise downtime.
• Monitor the availability and performance of data systems and tools, ensuring they meet operational standards.

Collaboration and Communication

• Work closely with the Data Operations Lead, Data Engineering, Business Intelligence, Analytics, and Business teams to support data initiatives.
• Collaborate with vendors and partners for data-related services as directed by the Data Operations Lead.
• Communicate effectively with team members and stakeholders to ensure alignment on data projects and initiatives.

Compliance and Security

• Assist in ensuring compliance with various jurisdictions and regulations, as well as industry best practices.
• Implement and maintain data security measures to protect sensitive information.
• Participate in regular audits and assessments to identify and mitigate risks.

Day-to-Day Activities

• Check the status of data jobs to ensure they are running as expected and troubleshoot any issues.
• Monitor and maintain data pipelines, ensuring data flows smoothly between systems.
• Conduct data verification and integrity checks to maintain high data quality and accuracy.
• Perform reconciliations across various data sources to identify and resolve discrepancies.
• Proactively perform data audits to ensure data accuracy and compliance.
• Suggest and build improvements in data accuracy and reconciliation frameworks.
• Work collaboratively with the data team to address any operational challenges and support data-driven initiatives.

On-Call Rotations

• On-Call Rotations - During specific weeks, you need to be available 24/7 in case of incidents.

✅ Requirements:

• At least 3 years of Python engineering experience;
• At least 2 years of experience with SQL;
• 1+ years of experience in data management and data operations roles.
• Proficiency in SQL, Python, or other data manipulation languages.
• Experience with cloud data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
• Familiarity with ETL tools (e.g., Apache NiFi or Airflow).
• Knowledge of cloud platforms (AWS, Azure, Google Cloud).
• Strong problem-solving skills and attention to detail.
• At least 1 year of experience in PowerBI (or similar);
• Excellent communication and teamwork skills.

Nice to have:

• Experience with data quality management.
• Experience working with agile.
• Understanding of data governance frameworks and practices.
• Certifications in relevant data management or cloud platform technologies.

✅ We offer excellent benefits, including but not limited to:

✔️24 days of vacation per year;

✔️Private Health Insurance;

✔️Daily Breakfasts and Friday lunches in the office;

✔️Snacks in the Office;

✔️Transport Allowance of up to 150 euro paid quarterly (public transport or taxi);

✔️Gym Subsidies for office building gym;

✔️Tennis or Paddle Training sessions reimbursement, up to 100 EUR monthly;

✔️Discount for Premium subscription for Cloudigo;

✔️Discounts at partners of the company;

✔️Annual salary reviews;

✔️Birthday gifts;

✔️Option for parking;

✔️Regular office & team building events.

❗️Please note that this role is office based for Valencia, Spain (RAS Valencia - Servicios Profesionales de Recursos Humanos).

❗️We can provide relocation assistance if you're outside of the city or country.

We’re looking for a highly skilled Data Architect with experience in data warehousing to design and optimize our data platform. You’ll play a critical role in shaping our data ecosystem—defining architecture, ensuring scalability, and enabling advanced analytics and reporting across the organization.

Key Responsibilities

• Design and implement scalable, secure, and high-performance data architectures on AWS using Snowflake as the central data warehouse;
• Design and optimize ELT/ETL pipelines using tools such as Airflow and Snowflake Streams and Procedures;
• Lead the design of data models (Star/Snowflake schema) and data marts for analytics and operational reporting;
• Work with data engineers, BI, and other technical teams and business stakeholders to understand requirements and translate them into technical data solutions;
• Establish data governance, cataloging, and lineage practices;
• Ensure compliance with data security, privacy, and regulatory standards;
• Drive performance tuning, cost optimization, and best practices in Snowflake and across the data stack;
• Document architectural decisions and technical designs for team collaboration and future scalability.

Requirements

• 4+ years of experience in data engineering or architecture roles;
• Strong experience with AWS cloud services such as S3, Redshift, Glue, Lambda, IAM, and CloudFormation/Terraform;
• Proficiency in SQL, Python, and modern data pipeline frameworks (e.g., dbt, Airflow);
• Solid understanding of data modeling, data warehousing principles, and dimensional design;
• Experience with CI/CD practices and infrastructure as code in a data environment;
• Excellent communication and documentation skills.

Nice to Have

• Hands-on experience with Snowflake (warehousing, performance tuning, data sharing);
• Experience integrating with BI tools like Power BI or Tableau;
• Knowledge of data lake architecture and streaming technologies (Kafka, Kinesis);
• Certifications in Snowflake or AWS (e.g., SnowPro Core, AWS Data Analytics Specialty).

✅ Why you should join us?