Data Engineer II

Job description

The Company:

AudienceView is an organization of people who are passionate about the business of Live Events.

We create industry-leading software solutions that fuel attendee engagement, ticket sales and advertising solutions for thousands of sports, music and theatre venues in 16 countries around the world.

AudienceView employees share a vision to help entertainment organizations deliver exceptional experiences for people who love live events.

We achieve this through innovative technology, popular media brands, effective distribution strategies and a dedicated team of experts that help create customer success every single day.

Why We'd Want to Work with You:

As a Data Engineer II, you will be a key technical contributor responsible for building, optimizing, and maintaining the data infrastructure that powers our analytics and business intelligence capabilities.

You will bring strong expertise in cloud-based data engineering, with deep hands-on experience in the Azure ecosystem and modern data platforms.

Your problem-solving mindset and attention to detail drive the success of every pipeline you build and every optimization you implement.

You must possess a unique blend of technical depth and practical experience, understanding how data flows from raw ingestion through transformation pipelines to consumption in reports and dashboards.

You thrive in collaborative environments where clear communication, thorough documentation, and adherence to version control processes are essential.

You're someone who gets it, a hands-on engineer who understands the full data lifecycle and can trace data lineage from Power BI reports back through semantic models, Synapse, Python codebases, all the way to raw ingested data.

You're comfortable working within established processes while also identifying opportunities for improvement.

You know when to dig deep to solve complex problems independently, and you know when to ask for help—both are equally important.

What You'll Do

• Design, build, and maintain scalable data pipelines using Azure Data Factory, Databricks, and Synapse to support analytics and reporting needs.
  
  
• Develop and optimize data transformation logic using Python, PySpark, and SQL, ensuring performance, reliability, and data quality.
  
  
• Optimize Spark jobs and Databricks workflows for performance and cost-efficiency, applying best practices for distributed data processing.
  
  
• Work with Azure services including ADLS Gen2, Key Vault, Event Hubs, and other data-focused Azure services to build robust data infrastructure.
  
  
• Manage and maintain Databricks Hive metastores, with opportunities to contribute to Unity Catalog implementation and leverage modern Databricks features such as Metric Views and structured streaming.
  
  
• Process and transform JSON messages from Kafka and other streaming sources, ensuring reliable data ingestion.
  
  
• Collaborate with the analytics team to understand data requirements and trace data lineage from Power BI reports through semantic models, Synapse, and transformation code back to raw data sources.
  
  
• Maintain code and projects in git repositories using VS Code, adhering to version control best practices including branch management and working with Power BI projects in PBIP format.
  
  
• Document work in progress and completed tasks using Azure DevOps (Kanban boards, wiki), ensuring clear communication and knowledge sharing across the team.
  
  
• Evaluate and contribute to the adoption of new Azure services and platforms such as Fabric/OneLake as the team explores enhancements to the data architecture.
  
  
• Collaborate with the Senior Data Engineer and broader team to identify and implement improvements to data pipelines, ingestion architecture, and overall data platform capabilities.
  
  

What You'll Need

• Minimum 5+ years of experience as a Data Engineer, with strong hands-on expertise in Azure cloud services and modern data platforms.
  
  
• Deep experience with Azure Databricks, including Spark optimization and working with Hive metastores.
  
  
• Proficiency in Spark optimization techniques for performance tuning and cost management in distributed data processing environments.
  
  
• Hands-on experience with Azure Data Factory for building and orchestrating data pipelines.
  
  
• Experience with Azure Synapse for data warehousing and analytics workloads.
  
  
• Strong SQL skills for data manipulation, transformation, and analysis.
  
  
• Proficiency in Python and PySpark for data engineering tasks, transformations, and pipeline development.
  
  
• Experience with Azure ADLS Gen2, Key Vault, and Azure DevOps (Kanban boards, wiki, branch management).
  
  
• Experience working with JSON messages produced by Kafka or similar streaming platforms.
  
  
• Some knowledge of Power BI, including the ability to trace data lineage from reports through semantic models back to data sources, understanding how analytics consume the data you engineer.
  
  
• Comfort with VS Code and git for version control, including experience managing Power BI projects in PBIP format and adhering to collaborative development processes.
  
  
• Problem-solving mindset with the ability to diagnose complex data issues, QA, troubleshoot pipeline failures, and optimize performance.
  
  
• High attention to detail, ensuring data quality, accuracy, and reliability across all pipelines and transformations.
  
  
• Strong collaboration and communication skills, including comfort with documentation, clear status updates, and working within processes that support team collaboration.
  
  
• Self-awareness and judgment about when to work independently and when to seek help recognizing that both are critical to success.
  
  
• Ability to work independently while also thriving in a collaborative team environment.
  
  

Nice to Have

• Familiarity with Unity Catalog and recent Databricks features (Metric Views, structured streaming)
• Familiarity with Event Hubs or similar streaming/ingestion services, as the team evaluates alternatives to current ingestion architecture.
  
  
• Awareness of Microsoft Fabric/OneLake, as these platforms are under consideration for future adoption.
  
  
• Bachelor's degree in computer science, Engineering, Information Systems, or a related technical field
• Experience in the ticketing or live event industry

Why Work at AudienceView:

• We're a global leader in live events technology.
  
  As the essential partner to get live events discovered, attended, and remembered, we help our clients sell more tickets every single day.
  
  
• We're passionate about live entertainment.
  
  AudienceView believes in the power of live events and its purpose is to ignite that passion in people around the world.
  
  
• We have amazing clients.
  
  Our exciting roster of clients includes sports, live music, and performing arts organizations
• Our employees love us.
  
  We offer excellent benefits, competitive salaries, flexible hours, remote work opportunities, and more
• We're a remote-first company.
  
  Our remote culture allows our employees to have the flexibility to work anywhere in the country they are residing (Canada, the USA, UK, and Chile).
  
  
• Diversity and inclusion are paramount to building our culture.
  
  The data is abundantly clear that diverse teams are more successful because they offer different perspectives, increased innovation, faster problem-solving, and higher employee engagement among other benefits.
  
  
• Flexible work schedule: AudienceView empowers permanent employees to take off alternating Fridays by condensing their two-week schedule into 9 days.
  
  Flexible, uncapped vacation and sick policy.
  
  Employees need time away from work to recharge.
  
  

How we hire - here's a brief overview of our recruitment process:

• Screening & Resume Review:
   Our Talent Acquisition team will evaluate all resumes and select candidates for a video screening call for 30 minutes.
  
  
• Hiring Manager Interview (60 minutes):
  Meet with the hiring manager to speak in detail about your relevant experience and learn more about the role.
  
  
• Meet More of the Team (60 minutes):
  Meet more Data & Analytics Team to learn more about the work culture and the expectations.
  
  
• Final Interview (60 minutes):
   Showcase your technical skills as a Data Engineer in a final case-study interview.
  
  

Diversity and inclusion have always been at the core of our values at AudienceView.

A diverse workforce with wide perspectives and creative ideas benefits our clients, the communities where we operate, and all of us as colleagues.

We welcome applications from qualified individuals from all backgrounds.

We also welcome and encourage applications from people with disabilities.

Accommodations are available on request for candidates taking part in all aspects of the recruitment process.

Disclaimer:

AudienceView does not offer employment to prospects without first ensuring that qualified candidates speak directly with the hiring manager and a member of our HR team.

All qualifications will be done face-to-face over Microsoft Teams.

AudienceView does not send out offers of employment without meeting candidates and does not offer employment via text.

If you are requested for any personal information via text and/or without having met a member of our hiring team in person, please disregard.

Required Skill Profession

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