Audinate

Professional AV networking via Dante platform

Data Engineer

Data EngineeringConfirmed live in the last 24 hours

Full-timeManila, Metro Manila, Philippines

About the Job

Requirements

Deep experience in analytics engineering or data engineering, ideally within a B2B technology business.
Strong analytics engineering practices, with version control, peer review, testing, and documentation integrated into the workflow.
Hands-on skills in Python, SQL, and NoSQL, such as MongoDB, and the ability to write well-structured, maintainable code.
Practical experience building end-to-end data pipelines covering ingestion, transformation, scheduling, and monitoring, using modern tools such as dbt, Airflow, Dagster, Prefect, or similar.
Experience with a modern cloud data warehouse such as Snowflake, BigQuery, Databricks, or Redshift, including making it accessible and safe for self-service use across the organization.
Experience with a modern BI or reporting tool such as Metabase, Superset, Looker, Sigma, or Lightdash, and the ability to build dashboards used by non-technical users.
Comfort with light platform and infrastructure work, such as container basics, scheduled jobs, secrets management, and core cloud services such as AWS, Azure, or GCP.
Clear written communication skills to document pipelines and metric definitions for engineers and business users.
Sound judgment about when to seek direction and when to make decisions independently.
A tertiary qualification in a relevant field, such as computer science, engineering, mathematics, statistics, or information systems, or equivalent experience.

Responsibilities

Build and maintain data pipelines that ingest, transform, and prepare commercial and operational data for analysis.
Develop and maintain the modelled data layer, including version control, peer review, testing, and documentation.
Create and maintain reporting tools, including dashboards, scheduled reports, and self-service exploration powered by large language model-based tools, for Sales, Marketing, Finance, Product, and Strategy teams.
Turn exploratory analyses into robust, supportable data products that continue to deliver commercial value.
Handle platform and lightweight infrastructure work, including orchestration, deployment, monitoring, and data quality checks, in partnership with the internal DevOps team.
Work within the platform roadmap and recommend tooling and modelling approaches.
Partner closely with the team's data scientist.

Desired Qualifications

Experience bringing artificial intelligence or large language model tools into data workflows for data enrichment, documentation, or analytical support.
Experience with business systems such as customer relationship management platforms, including Salesforce or HubSpot, and accounting platforms such as NetSuite.
Familiarity with the professional AV industry or hardware-software businesses that sell through an original equipment manufacturer channel.

Find Your Connection to Endless Possibilities

Are you a data engineering professional looking for the next step in your career? If the opportunity to work in a global industry leader with a diverse culture excites you, this may be the role for you.

With Audinate, you’ll find your connection to the world of sound and vision.

We lead the world in AV networking media to pioneer the way people see and hear. Our products seamlessly manage hundreds of audio and video channels with one network, making us the industry standard. You’ll find us in the largest companies and institutions like the Sydney Opera House, NFL Media Headquarters, Microsoft, and even a 900-year old cathedral featured in Harry Potter.

Our core values are the foundation of everything we do: Excellence, Courage, Integrity, Innovation, and Teamwork.

If this resonates with you, this is the place for you.

What you’ll experience with us

No matter your role, you’ll feel part of our team and contribute to pioneering the future of AV so that everyone can be seen and heard. In addition to a competitive salary, annual bonus and equity incentive plan you’ll be part of our diverse, values-based culture. You’ll also enjoy a range of benefits such as flexible working (2 days per week in office), home office support, and volunteering leave.

About the role

As our Data Engineer, you’ll turn the data our business depends on into pipelines, models, and reports that people can trust every day. Your mission is to make our data products last: well-engineered, documented, tested, and easy to operate, so the insights we produce build on each other over time.

You’ll work alongside a senior data scientist and report to our Data & Insights Manager. Within the team, you’ll own the analytics engineering craft end to end: this means building the pipelines that move and shape our data, designing the models the business uses to make decisions, and creating the dashboards that Sales, Marketing, Finance, Product, and Strategy rely on to run their day-to-day operations.

What you'll be doing

Building and maintaining the data pipelines that bring in, transform, and prepare Audinate’s commercial and operational data for analysis.

Developing and looking after our modelled data layer (e.g. dbt), the foundation the business uses to understand itself, with version control, peer review, testing, and documentation built into how you work.

Creating and maintaining the reporting tools our internal customers rely on to run their work, including dashboards, scheduled reports, and self-service exploration powered by LLM-based tools, for teams across Sales, Marketing, Finance, Product, and Strategy.

Turning the team’s proven exploratory analyses into robust, supportable data products that keep delivering commercial value.

Handling the platform and lightweight infrastructure work that keeps our stack running smoothly, including orchestration, deployment, monitoring, and data quality checks, in partnership with our internal DevOps team.

Working within the platform roadmap while bringing your own recommendations on tooling and modelling approaches.

Partnering closely with the team’s data scientist.

What we're looking for

Deep experience in an analytics engineering, data engineering ideally within a B2B technology business.
A track record of strong analytics engineering practice, where version control (git), peer review, testing, and documentation are built into your workflow rather than added at the end.
Strong hands-on skills in Python, SQL, and NoSQL (e.g. MongoDB), with code that’s well structured and easy for others to pick up and run with.
Practical experience building end-to-end data pipelines, covering ingestion, transformation, scheduling, and monitoring, using modern tools such as dbt, Airflow, Dagster, Prefect, or similar.
Experience working with a modern cloud data warehouse (e.g. Snowflake, BigQuery, Databricks, Redshift), including setting it up so others across the organisation can use it easily and safely on a self-service basis.
Experience with a modern BI or reporting tool (e.g. Metabase, Superset, Looker, Sigma, Lightdash), and the ability to build dashboards that non-technical users genuinely use.
Comfort taking on light platform and infrastructure work, such as container basics, scheduled jobs, secrets management, and core cloud services (AWS, Azure, or GCP).
Clear written communication skills, so you can document a pipeline or metric definition in a way the next person, whether an engineer or a business user, can understand without needing you.
Sound judgement about when to seek direction and when to make the call yourself.
A tertiary qualification in a relevant field (e.g. computer science, engineering, mathematics, statistics, information systems), or equivalent experience.

Nice to have

Experience bringing AI or LLM tools into the data workflow, whether for data enrichment, documentation, or analytical support.

Experience working with business systems such as CRMs (e.g. Salesforce, HubSpot) and accounting platforms (e.g. NetSuite).

Familiarity with the professional AV industry, or with hardware-software businesses that sell through an OEM channel.

If you're a Data Engineer or Analyst looking for an opportunity to make a difference we may be on the same wavelength.

Apply now and submit your CV and cover letter.

About the Company

Audinate

Professional AV networking via Dante platform

Audinate licenses its Dante technology to original equipment manufacturers, enabling professional AV gear to distribute high-quality, uncompressed audio and, with Dante AV, video signals over standard Ethernet. The system works by embedding Dante software and hardware into devices (chips and modules) and using applications like Dante Controller to route and Dante Virtual Soundcard to link computers to a Dante network. Its differentiator is a broad, interoperable ecosystem that lets many manufacturers’ devices work together on the same network for low-latency, reliable signal distribution, now expanding from audio to video. The goal is to enable scalable, reliable AV networking across broadcast, installation, live sound, and recording by growing adoption of Dante and Dante AV.

Company size: 201-500
Company stage: IPO
Headquarters: Sydney NSW, Australia
Founded: 2006

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