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Aylo

Data Developer

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
Posted

Original job description

Established in 2004, we are a tech pioneer offering world-class adult entertainment and games on some of the internet’s safest and most popular platforms. With the support of an international team of dynamic and collaborative innovators, we are on a mission to enable safe user experiences and empower our communities by celebrating diversity, inclusion, and expression - all while maintaining robust trust-and-safety protocols.

We embrace the best of both worlds! Local talent can thrive in our collaborative office space with the flexibility of a hybrid work environment, while remote team members play an integral role in shaping our dynamic culture from afar. We have offices in Montreal (Quebec), Austin (Texas) and Nicosia (Cyprus).

  • A select number of positions require full-time in office attendance*

Make your mark in a role where strong analytics engineering directly supports critical operations at scale. You’ll tackle complex data challenges and help shape modern data practice. Join a focused, supportive team that cares about both outcomes and sustainability by helping to define how performance, resilience, security, and cost are measured across a large organization

What you'll be doing:

  • Build and maintain scalable data models and transformation pipelines for infrastructure, security, and operational analytics using SQL and modern data tooling
  • Treat the platform as code: version-controlled transformations, tested pipelines, peer-reviewed changes, and reproducible environments
  • Own the security data model, including entity resolution across asset and identity sources, a common cross-domain schema, and partitioning, retention, and cost strategy
  • Deliver curated datasets, semantic layers, and dashboards that make reporting on system performance, outages, security health, and cost consistent and trusted
  • Enforce data quality and governance through validation checks, freshness SLAs, reconciliation, lineage tracking, access controls, and sensitive-data handling
  • Partner with engineering, infrastructure, and security teams to define metrics, standardize definitions, and improve data accessibility
  • Analyze vendor performance and cost data to support infrastructure investment and optimization decisions
  • Improve the analytics platform itself: workflow orchestration, query performance, and architecture

Must haves:

  • 3+ years in analytics engineering, data analytics, or a similar technical role
  • Bachelor's degree in Statistics, Computer Science, Engineering, Finance, or a related analytical field
  • Strong SQL, plus experience building data models (dimensional modeling, warehousing, or data lake environments)
  • Hands-on experience with a transformation framework such as dbt, and with version control and reproducible data workflows
  • Experience with BI tools (Power BI, Tableau) and semantic layer design
  • Working knowledge of data quality, governance, and privacy practices
  • Experience with technical data domains such as infrastructure, systems, security, or engineering telemetry
  • Ability to translate complex technical data into insights stakeholders can act on

Nice to haves:

  • Python for data transformation, pipeline development, or analysis
  • Workflow orchestration tools (e.g., Airflow) and data lake table formats (Delta, Iceberg)
  • Understanding of cloud systems and observability metrics
  • Experience with vendor performance or financial analysis
  • AI/ML governance frameworks and associated data controls
  • End-to-end MLOps: feature engineering on large-scale telemetry (pandas/Polars, PySpark), anomaly detection and classification models (scikit-learn, XGBoost, PyOD), and experiment tracking with a versioned model registry (MLflow)

As an equal opportunity employer, we celebrate diversity and are committed to creating an inclusive environment for all employees

In this role you may be exposed to adult content
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More about this job

Responsibilities

Build and maintain scalable data models, transformation pipelines, curated datasets, semantic layers, and dashboards for infrastructure, security, and operational analytics. Establish trusted data practices through quality controls, governance, security, and cost strategies, while partnering with technical teams to define metrics and improve the analytics platform.

Requirements

Requires at least three years of experience in analytics engineering, data analytics, or a similar technical role, plus a bachelor's degree in a relevant analytical field. Candidates need strong SQL and data modeling skills, hands-on experience with dbt or a similar transformation framework, BI and semantic layer experience, and working knowledge of data quality, governance, privacy, and technical data domains.

Skills

  • SQL
  • Analytics Engineering
  • Data Modeling
  • Data Transformation
  • dbt
  • Version Control
  • Data Warehousing
  • Dimensional Modeling
  • Business Intelligence
  • Semantic Layer Design
  • Data Quality
  • Data Governance
  • Data Privacy
  • Python
  • Workflow Orchestration
  • Stakeholder Communication

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Software
  • Security & Safety

Keywords

  • SQL
  • dbt
  • Python
  • Power BI
  • Tableau
  • Airflow
  • Delta
  • Iceberg
  • PySpark
  • Pandas
  • Polars
  • Scikit-Learn
  • XGBoost
  • PyOD
  • MLflow
  • Analytics Engineering
  • Data Modeling
  • Dimensional Modeling
  • Data Warehousing
  • Data Lakes
  • Semantic Layers
  • Data Quality
  • Data Governance
  • Data Privacy
  • Workflow Orchestration
  • Cloud Systems
  • Observability
  • Infrastructure Analytics
  • Security Analytics
  • MLOps

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