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Data Engineering

Data, analytics and platform engineers - for the pipelines and warehouses your business actually runs on.

What We Place

The roles we run, by level.

  • Senior Data & Analytics Engineers
  • Data Platform Leads & Heads of Data
  • ML Data Infrastructure Engineers
  • Streaming & Real-time Data Engineers
  • Analytics Engineers (modern stack)
  • Stack: dbt, Snowflake, Databricks, Airflow, Spark, Kafka

Where The Talent Sits

The pools we actually source from.

  • Modern-stack consultancies (Servian, Stax, Mantel Group)
  • Cloud-native scale-ups with mature data practices
  • Big-tech data org alumni (Atlassian, Canva, Afterpay)
  • Specialist platforms: Databricks, Snowflake, Confluent ANZ
  • PhDs and applied-stats backgrounds in lakehouse architectures

Geographies

Sydney and Melbourne primary. Remote-Australia common across the modern stack.

Comp Bands (2026)

Senior IC: $180k - $280k base. Platform Leads: $230k - $340k base. Heads of Data: $300k - $420k base + bonus + equity.

Median Brief - Signed

21 days. 90% of mandates filled in ≤3 CVs.

How We Run The Search

Four steps. Twenty-one days.

01

Brief

90 minute working session. Scorecard signed off before any outreach.

02

Search

Direct outreach across APAC, EMEA and US. 200-400 named engineers per mandate.

03

Shortlist

3-5 calibrated candidates, each with a one-page technical memo.

04

Close

Pre-closed comp, counter-offer coaching, replacement guarantee.

Recent Data Searches

Indicative of where we run.

Indicative samples drawn from recent and active mandates. Specific clients available under NDA on request.

Further reading

Related insights.

Salary

Data Engineering Compensation Trends

Market Signals

Tech Hiring in Australia: Q1 2026 Monthly Snapshot

Hiring Process

What a Structured Intake Call Should Actually Cover

Common questions

Frequently asked.

What data engineering roles do you recruit?

Data engineers, analytics engineers, data platform engineers, ML data engineers and heads of data. Common stacks include Snowflake, BigQuery, dbt, Spark, Kafka, Airflow, and modern data lakehouse architectures.

What salary bands are typical for senior data engineers in 2026?

Senior data engineer base sits at AUD 160-190k in Sydney for 2026, base only, 25th-75th percentile of accepted offers. Principal data engineers reach AUD 190-250k and tech leads AUD 200-250k.

Do you cover analytics engineering and data platform separately?

Yes. Analytics engineering (dbt, transformation logic, business-facing modelling) and data platform engineering (Spark, Kafka, infra) are distinct profiles. Our intake process maps the brief to the correct profile rather than treating them as interchangeable.

What industries hire most frequently for senior data engineers?

Fintech, healthtech, retail/ecommerce, energy, and AI-native startups are the most active sectors for senior data engineering hires in Australia.

Can you recruit for ML data engineers and feature platform roles?

Yes. ML data engineering, feature platforms, and ML observability are growing categories. We have placed in this profile across both AI-native scale-ups and large enterprise teams.

How do you screen data engineers before shortlisting?

A 20-30 minute live conversation covering pipelines and warehouses they have owned end to end, how they handled schema evolution and data quality at scale, and their position on the analytics-engineering versus platform spectrum. No unscreened profiles.

What do data engineering contractors charge in 2026?

Senior data engineer day rates in Sydney run AUD 950-1,150 excluding GST. Contract demand is driven by platform migrations and cloud modernisation programs.

What is the most common mistake in data engineering briefs?

Conflating analytics engineering with data platform engineering. They price similarly but source from different pools. A brief that asks for deep dbt modelling plus Kafka streaming infrastructure usually needs two hires, not one.

How long does a senior data engineering search take?

21 days median from intake to signed offer, with calibrated shortlists inside 72 hours. ML data engineering briefs can run slightly longer because the intersection pool is newer.

Submit a brief

Run a structured Data search.

30 minute working session. No fee until placement. Replacement inside 90 days.

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