Data Engineer
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Before you apply
LocationManila
Work modehybrid
Typefull-time
SeniorityMid
DepartmentOperations, Data & Insights
EquityIncluded
Company size201–500 people
PostedNov 2, 2026 · 2d ago
Verified live2d ago
At a glanceSummarised by Seekless from the posting.
Deep experience in 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
Strong hands-on skills in Python, SQL, and NoSQL (e.g. MongoDB)
Practical experience building end-to-end data pipelines 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)
Experience with a modern BI or reporting tool (e.g. Metabase, Superset, Looker, Sigma, Lightdash)
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
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
Experience bringing AI or LLM tools into the data workflow
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
Skills
Python
SQL
NoSQL
MongoDB
dbt
Airflow
Dagster
Prefect
Snowflake
BigQuery
Databricks
Redshift
Metabase
Superset
Looker
Sigma
Lightdash
AWS
Azure
GCP
git
LLM
Salesforce
HubSpot
NetSuite
Benefits
Competitive salary
Annual bonus
Equity incentive plan
Flexible working
Home office support
Volunteering leave
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
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Building and maintaining the data pipelines that bring in, transform, and prepare Audinate’s commercial and operational data for analysis.
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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.
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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.
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Turning the team’s proven exploratory analyses into robust, supportable data products that keep delivering commercial value.
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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.
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Working within the platform roadmap while bringing your own recommendations on tooling and modelling approaches.
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Partnering closely with the team’s data scientist.
What we’re looking for
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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
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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.
Hiring process
Apply now and submit your CV and cover letter.