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Senior Data Engineer

Role overview

Qualifications

  • 5+ years of experience with Python, preferably including 2+ years working with Airflow
  • 5+ years of experience with SQL in big data environments, preferably including 2+ years with dbt
  • 4+ years in cloud environments, preferably with 2+ years each in Snowflake and AWS
  • 2+ years of experience with data streaming platforms, preferably on Kafka

Responsibilities

  • Design and implement robust, scalable data architecture to support the collection, storage, and processing of large volumes of igaming and customer data
  • Build and maintain efficient ETL and ELT processes to ensure seamless data ingestion from multiple sources into our data lake, DWH, and final consumers
  • Create and maintain well-structured data models that ensure accuracy, integrity, and optimal performance for analytical use cases following Kimball best practices
  • Collaborate with cross-functional teams to integrate data across systems

About the company

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Ventures Lab

Company details

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Job description

ABOUT US:

Ventures Lab is an international company with over 200 employees, specializing in the iGaming and Fintech industries. We deliver a diverse portfolio of products and services, including iGaming verticals, electronic payment solutions, and managed services for customer operations. By leveraging technology and driving innovation, we empower our partners to achieve greater success in competitive markets. Our global reach and expertise make us a trusted partner for cutting-edge solutions.


THE ROLE:

The Senior Data Engineer is responsible for designing, building, and maintaining scalable data infrastructure that enables reliable data collection, processing, integration, and analysis across the business. The role ensures that data pipelines, models, and platforms are robust, secure, efficient, and aligned with business and regulatory requirements.


Reporting to the Head of Data, the Senior Data Engineer plays a key role in developing batch and real-time data solutions, supporting data architecture, improving data quality and governance, and automating data workflows. The position contributes to the stability, performance, and scalability of the company’s data ecosystem, enabling teams across the organisation to access accurate and timely data for operational and strategic decision-making.


RESPONSIBILITIES:

  • Data Architecture: Design and implement robust, scalable data architecture to support the
    collection, storage, and processing of large volumes of igaming and customer data.
  • ETL Development: Build and maintain efficient ETL and ELT processes to ensure seamless data
    ingestion from multiple sources into our data lake, DWH, and final consumers.
  • Data Modeling: Create and maintain well-structured data models that ensure accuracy,
    integrity, and optimal performance for analytical use cases following Kimball best practices.
  • Data Integration: Collaborate with cross-functional teams to integrate data across systems,
    with several types of integration as API, Kafka, DB extractions, Webscrapping, Email, etc.
  • Streaming & Real-Time Processing: Develop and manage real-time data pipelines using
    streaming technologies (e.g., Kafka) to support time-sensitive use cases.
  • Data Quality & Governance: Enforce data governance policies and best practices, ensuring
    high standards for data quality, security, and regulatory compliance.
  • Performance Optimization: Continuously monitor, troubleshoot, and optimize data pipelines,
    queries, and infrastructure for speed, efficiency, and reliability.
  • Pipeline Orchestration: Support and expand production-grade orchestration workflows using
    Apache Airflow.
  • Observability & Monitoring: Set up and maintain monitoring, alerting, and observability for
    data pipelines and systems using tools like Elementary, Datadog, Prometheus, or Grafana.
  • CI/CD and Automation: Develop and maintain CI/CD pipelines for data projects using
    Bitbucket Pipelines or GitHub Actions, ensuring streamlined deployment and testing
    processes.
  • Version Control & Collaboration: Follow best practices in Git-based version control and work
    collaboratively in a modern DevOps environment.

QUALIFICATION, SKILLS & EXPERIENCE:

  • 5+ years of experience with Python, preferably including 2+ years working with Airflow.
  • 5+ years of experience with SQL in big data environments, preferably including 2+ years with
    dbt.
  • 4+ years in cloud environments, preferably with 2+ years each in Snowflake and AWS.
  • 2+ years of experience with data streaming platforms, preferably on Kafka.
  • 2+ years of hands-on experience with containerization (Docker, Kubernetes).
  • 3+ years managing CI/CD pipelines, ideally using Bitbucket Pipelines or GitHub Actions.
  • Deep understanding of data governance, data quality, and data lineage principles.
  • Proficient in using monitoring and alerting tools such as Datadog, Prometheus, or Grafana.
  • Solid experience with version control tools (Git) and IaaS (e.g., Terraform).
  • Strong communication and problem-solving skills, with a proactive and self-driven attitude.


OUR OFFER:

  • Competitive salary synonymous with skills and experience,
  • Performance and bonus structure dependent on achievement of set targets and personal performance,
  • The opportunity to making a real impact at a time of rapid growth
  • Consultancy B2B contract on a full time basis with 25 days PTO


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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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