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Software Engineer, Data Platform Product

Remote (EST timezone) • Remote • Full-time Contract • Req ID: GDBI-1K3M5H9J

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Software Engineer, Data Platform Product

Location: Remote (EST preferred) • Type: Full-time • Status: Open
About Global Data and BI Global Data and BI is hiring on a rolling basis for Data, BI & Analytics and ML/AI projects for large corporations. Beyond consulting services, we build production-ready business platforms and SaaS applications that leverage modern cloud technologies, data analytics, and AI capabilities. We deliver enterprise-grade solutions with certified engineers in AWS and Microsoft Azure / Power BI technologies. Our focus includes transformation projects in the financial industry, custom platform development, and our proprietary Noème suite of products. Our mission is to transform the corporate data journey from complexity to strategic clarity, ensuring data is not just collected, but leveraged to drive smarter decisions, stronger businesses, and lasting impact.

Summary

Millions of enterprise users depend on the data platforms and analytics systems we build. The Data Platform Product team is responsible for designing, implementing, scaling, and operating the foundational data infrastructure that powers our Noème product suite and client platforms. You'll join a team of talented engineers building best-in-class data capabilities that enable data-driven decisions, real-time analytics, AI/ML workflows, and mission-critical business applications for Fortune 500 clients.

Our data platforms power everything from real-time event processing and analytics dashboards to AI-powered automation, data integration pipelines, and enterprise data warehouses. You'll build systems that process millions of events daily, enable complex data transformations, and deliver insights that drive business decisions across global organizations.

What you'll do (roles & responsibilities)

  • Own and develop systems that democratize data access and enable advanced analytics capabilities for Noème products and client platforms
  • Build scalable data infrastructure including event streaming platforms, data pipelines, workflow orchestration, and real-time processing systems
  • Design and implement data platform features that power product capabilities like real-time analytics, AI/ML workflows, automated data quality checks, and intelligent notifications
  • Work cross-functionally with Product, Data Science, Data Engineering, AI, and Client Success teams to deliver impactful data solutions
  • Work across the full stack - from cloud infrastructure (Azure/AWS) to backend services to data processing frameworks - to successfully build and deliver platforms that provide leverage to multiple teams
  • Influence and execute the roadmap for data infrastructure and systems that power high-scale product features using real-time and batch data processing
  • Monitor and operate systems in production environments, optimizing performance, ensuring reliability, and evolving critical systems with minimal disruption
  • Build event-based architectures that handle millions of events per day with high throughput, low latency, and strong reliability guarantees
  • Design asynchronous workflow systems for complex data processing, ETL/ELT pipelines, ML model training, and business automation
  • Implement data integration patterns connecting diverse data sources (databases, APIs, SaaS platforms, streaming sources) into unified data platforms
  • Create reusable tools and frameworks that enable data engineers and product teams to build data-powered features efficiently
  • Ensure data quality and governance by building monitoring, validation, and lineage tracking capabilities into data platforms
  • Optimize cost and performance of cloud data infrastructure while maintaining high availability and scalability
  • Collaborate with clients to understand their data requirements and deliver custom platform capabilities that solve their business challenges
  • Contribute to technical architecture decisions and help establish best practices for data platform development
  • Mentor junior engineers and contribute to building a strong engineering culture

What you should have (Must-Haves)

  • Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience
  • 5+ years of software engineering experience with 3+ years focused on data infrastructure, data platforms, or backend systems at scale
  • Deep expertise in building scalable systems: You have worked on data or infrastructure-focused engineering teams that own substantial software platforms. You've experienced scaling systems through multiple orders of magnitude of growth
  • Strong programming skills in languages like Python, Java, Scala, or Go for building production-grade data systems
  • Experience with cloud platforms (Azure and/or AWS) including services for data processing, storage, and orchestration (e.g., Azure Data Factory, Databricks, Synapse, AWS Glue, EMR, Redshift)
  • Knowledge of event streaming and messaging systems (Kafka, Azure Event Hubs, AWS Kinesis, Pulsar) and experience building event-driven architectures
  • Experience with asynchronous workflow systems and job orchestration (Airflow, Prefect, Temporal, Azure Data Factory, AWS Step Functions)
  • Understanding of data modeling for both analytical and operational workloads, including data warehouses, data lakes, and real-time systems
  • Experience with databases (PostgreSQL, MySQL, SQL Server) and distributed systems (Redis, Cassandra, MongoDB)
  • Strong problem-solving skills: You can decompose complex problems and work towards clean solutions independently or with teammates
  • Pragmatic and business-oriented: You care about business impact and prioritize accordingly, balancing craft, speed, and outcomes
  • Empathetic communication: You communicate technical decisions clearly in writing and verbally, collaborate effectively, and disagree and commit when needed
  • Production operations experience: You understand monitoring, alerting, performance optimization, and operating systems at scale
  • Team player: You enjoy collaborating cross-functionally and helping others learn and grow

Nice-to-Haves

  • Experience building data platforms at fast-growing startups or scale-ups, particularly ones serving enterprise clients
  • Deep experience with specific streaming technologies like Apache Kafka, Flink, or Spark Streaming in production environments
  • Full-stack development experience with TypeScript, Node.js, React for building data platform UIs and internal tools
  • Experience with modern data stack tools (dbt, Fivetran, Airbyte, Snowflake, Databricks) and understanding of ELT patterns
  • ML/AI platform experience including model training pipelines, feature stores, model serving, and MLOps practices
  • Infrastructure as Code expertise (Terraform, Pulumi, ARM templates) for managing cloud data infrastructure
  • Container orchestration experience with Kubernetes or similar platforms for running data workloads
  • Data governance and compliance experience, particularly in regulated industries like financial services
  • Experience with Power BI, Tableau, or other BI platforms and their underlying data architectures
  • API design and development for exposing data platform capabilities to product teams and clients
  • Performance optimization of data-intensive applications and large-scale distributed systems
  • Understanding of data security including encryption, access controls, and compliance requirements (SOC 2, GDPR, CCPA)
  • Open source contributions to data infrastructure or workflow orchestration projects
  • Experience working with financial services clients or other enterprise customers with complex data needs
  • Bilingual proficiency in English and French (asset for Quebec clients and bilingual platforms)

Work details

  • Location: Remote (EST timezone preferred for team collaboration)
  • Reporting relationship: You will report to the Engineering Manager or VP of Engineering

Compensation

Competitive salary package adjusted to your local market and country of residence. Compensation is location-based and reflects regional market standards. We benchmark against leading technology companies in your country to ensure competitive, fair pay for senior engineering talent.

Our commitment to diversity, equity, and inclusion We're committed to employment equity and encourage women, Indigenous Peoples, persons with disabilities, veterans and persons of all races, ethnicities, religions, abilities, sexual orientations, and gender identities and expressions to apply. We also welcome applications from Latin America countries, as the position is remote.

What happens after you apply

Timeline: We aim to complete our process within 2-3 weeks of application.

Step 1
Apply Submit your application. If you applied before and were not successful, you are welcome to apply again.
Step 2
Initial call (1 hour) If pre-selected, we schedule an initial conversation.
Step 3
Technical interview (1h30 to 2h) If shortlisted, you work through coding/system design problems with 2-3 engineers.
Step 4
Panel interview (1h to 1h30) Meet with Engineering and Product leads.
Step 5
Hiring decision If selected, we send an offer and next steps, otherwise we inform you by email.
If you don't hear back from us after application or any interview stage, it means we do not pursue your application.
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