Opportunity at
SEEKSenior Data Engineer
SEEK is seeking a Senior Data Engineer for its Marketing Technology group. This full-time post is listed as on-site. The person reports to the MarTech Data…
Career Tools
About This Role
SEEK is seeking a Senior Data Engineer for its Marketing Technology group. This full-time post is listed as on-site. The person reports to the MarTech Data and Insights Manager and joins a geographically spread APAC group of fourteen colleagues. The emphasis falls on modeling: shaping the data foundations that drive audience splitting, tailored experiences, analytics and campaign activation across ANZ and Asia. Core duties include examining source platforms, building abstract,…
Job Description
SEEK is seeking a Senior Data Engineer for its Marketing Technology group. This full-time post is listed as on-site. The person reports to the MarTech Data and Insights Manager and joins a geographically spread APAC group of fourteen colleagues. The emphasis falls on modeling: shaping the data foundations that drive audience splitting, tailored experiences, analytics and campaign activation across ANZ and Asia.
Core duties include examining source platforms, building abstract, logical, physical and dimensional schemas, and setting grain, keys, links and business vocabulary for warehouses and data marts. The engineer collaborates with pipeline builders to deploy these models through ETL/ELT workflows, relies on sophisticated SQL to confirm results, and works with source owners to fix quality gaps. Operational responsibilities extend to incident handling, observability, CI/CD and certain database administration tasks.
Applicants are expected to hold eight to ten years of modeling experience, ideally in warehousing, data marts or analytical platforms, along with a track record of shipping dimensional designs and pipelines. Working with Databricks would be appreciated but is optional.
Responsibilities
- Meet with stakeholders and analysts to pin down modeling approaches suited to each use case.
- Own design and documentation of abstract, logical, physical and multidimensional schemas.
- Settle entities, attributes, hierarchies and terminology alongside subject-matter experts.
- Inspect source systems, pair sources with targets, and flag gaps or transformation needs.
- Work with pipeline builders to ship dependable extract-transform-load processes.
- Apply advanced SQL to verify designs, explore datasets and diagnose faults.
- Tune model speed, query cost and physical layouts.
- Assist consumers in locating reliable data and resolve modeling or quality problems.
- Participate in incident response, alerting, deployment automation and database administration.
Requirements
- Eight to ten years of data modeling work, preferably in warehouses, data marts or analytical platforms.
- Demonstrable history of delivering conceptual through dimensional models end to end.
- Expert-level SQL for profiling, validating and debugging models and transformations.
- Good grasp of normal forms, denormalization, schema structure and performance tuning.
- Practical experience translating source data into targets and deploying models through ELT/ETL and orchestration tools.
- Hands-on exposure to large-scale tooling like Hadoop/EMR and Spark/Presto, or to MPP relational stores.
- Familiarity with AWS or another cloud data environment.
- Grasp of quality controls, governance, metadata and data lineage practices, plus some contact with MarTech products.
Qualifications
- Tertiary-level study in computing, IT or a closely related area.
- Background in distributed or remote team settings.
- Use of JIRA and Confluence for delivery work.
- Databricks know-how (beneficial) and some exposure to enterprise customer data platforms (helpful).
Core Skills
Benefits
- Yearly performance-related bonus scheme.
- Adaptable working arrangements that mix office attendance with home working, depending on the role.
- Regular gatherings such as sports days, an end-of-year party, a hackathon and trivia nights.
- Complimentary breakfast each morning, plus fruit available throughout the office.
- Relaxed dress code every day.
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is the post based?
The listing marks the position as on-site and covers ANZ and Asia, but it does not name a city.
How much background is expected?
Eight to ten years of data modeling experience, ideally in warehousing, data marts or analytical platforms.
Is Databricks mandatory?
No. Databricks skill is welcome but optional.
Is the post full time and what is the pay?
It is listed as full time. No salary is given.
How do I apply?
The listing does not describe an application process. It asks that unsolicited resumes and agency approaches not be sent.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.