Lead Consultant – Data Intelligence
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Before you apply
LocationMelbourne, Australia
Work modehybrid
Typefull-time
SeniorityLead
Experience7–10 yrs
DepartmentData Intelligence
Company size7+ people
PostedAug 17, 2026 · 2mo ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
7–10+ years in data engineering, data architecture, or analytics roles, with at least 3 years in a consulting or professional services environment
Proven track record of leading complex data platform deliveries end-to-end, with full accountability for outcomes
Deep hands-on AWS expertise: S3, Glue, Redshift, Athena, Lake Formation, Lambda, Kinesis, IAM, CloudWatch
Advanced proficiency in Databricks (Delta Lake, Unity Catalog, Spark optimisation)
Strong Python and/or Scala development skills for data engineering workloads at scale
Expert-level SQL with experience in query optimisation across distributed systems
Experience with dbt for transformation pipelines in production environments
Demonstrated experience engaging senior stakeholders (Director/VP/C-suite) and translating business strategy into data solutions
Strong commercial awareness — able to manage budgets, write proposals, and contribute to practice growth
Excellent written and verbal communication skills; confident presenting to both technical and executive audiences
Experience mentoring or leading small technical teams in a delivery context
AWS Certified Data Engineer – Associate or Professional, or AWS Solutions Architect – Professional
Databricks Certified Professional Data Engineer or Solutions Architect
DAG Development: competency writing and maintaining Directed Acyclic Graphs (DAGs) using native Apache Airflow operators
Exposure to data mesh, data products, or federated governance operating models
Familiarity with enterprise data governance platforms (Collibra, Alation, Atlan)
Experience with ML platform components (SageMaker, MLflow, Feature Store)
Knowledge of BI/visualisation tools: Tableau, Power BI, or AWS QuickSight
Unrestricted local working rights (Australia)
Skills
AWS
S3
Glue
Redshift
Lake Formation
Kinesis
Lambda
Step Functions
Databricks
Delta Lake
Unity Catalog
MLflow
Snowflake
Snowpark
Snowpipe
dbt
PySpark
SQL
Apache Airflow
Kafka
Spark Streaming
Figure
Athena
IAM
CloudWatch
Scala
Python
Tableau
Power BI
AWS QuickSight
SageMaker
Feature Store
Collibra
Alation
Atlan
Benefits
Technology allowance
Learning development budget
Professional development days
About the company
Cevo helps organisations build the capability for continuous evolution, turning transformation from a one-off program into a lasting ability to adapt, innovate and deliver better outcomes. As an Australian-owned, born in the cloud, AWS Premier Consulting Partner, we design and deliver modern cloud platforms, unlock data for insight and apply AI where it creates real value, while empowering teams so capability and impact extend well beyond each engagement. With onshore teams across Australia, we’ve partnered with more than 200 organisations across start-ups, commercial, enterprise and government.
Who are you?
As a Lead Data Intelligence Consultant at Cevo, you’ll need a combination of technical skills, strategic thinking, and effective communication.
Key Responsibilities:
•
Architect and oversee the implementation of scalable cloud data platforms on AWS using services including S3, Glue, Redshift, Lake Formation, Kinesis, Lambda, and Step Functions.
•
Lead solution design and technical governance across Databricks (Delta Lake, Unity Catalog, MLflow) and/or Snowflake (Snowpark, Snowpipe, data sharing, dynamic tables).
•
Define data modelling standards and patterns — star/snowflake schemas, medallion/lakehouse architecture, data vault — appropriate to client context.
•
Set and enforce engineering best practices: CI/CD for data pipelines, code review standards, testing frameworks, and documentation.
•
Oversee data transformation workstreams using dbt, PySpark, or SQL, ensuring quality and maintainability.
•
Guide platform and tooling selection decisions, producing clear business cases and technical trade-off analyses for clients.
•
Drive data governance, lineage, and cataloguing implementation using tools such as AWS Glue Data Catalog, Unity Catalog, or Collibra.
•
Provide architectural oversight on streaming and real-time data use cases (Kafka, Kinesis, Spark Streaming) where applicable.
•
Team Leadership & Mentoring
•
Contribute to pre-sales activities
Required Skills & Experience:
•
7–10+ years in data engineering, data architecture, or analytics roles, with at least 3 years in a consulting or professional services environment.
•
Proven track record of leading complex data platform deliveries end-to-end, with full accountability for outcomes.
•
Deep hands-on AWS expertise: S3, Glue, Redshift, Athena, Lake Formation, Lambda, Kinesis, IAM, CloudWatch.
•
Advanced proficiency in Databricks (Delta Lake, Unity Catalog, Spark optimisation)
•
Strong Python and/or Scala development skills for data engineering workloads at scale.
•
Expert-level SQL with experience in query optimisation across distributed systems.
•
Experience with dbt for transformation pipelines in production environments.
•
Demonstrated experience engaging senior stakeholders (Director/VP/C-suite) and translating business strategy into data solutions.
•
Strong commercial awareness — able to manage budgets, write proposals, and contribute to practice growth.
•
Excellent written and verbal communication skills; confident presenting to both technical and executive audiences.
•
Experience mentoring or leading small technical teams in a delivery context.
Desirable Skills & Certifications
•
AWS Certified Data Engineer – Associate or Professional, or AWS Solutions Architect – Professional.
•
Databricks Certified Professional Data Engineer or Solutions Architect.
•
DAG Development: competency writing and maintaining Directed Acyclic Graphs (DAGs) using native Apache Airflow operators
•
Exposure to data mesh, data products, or federated governance operating models.
•
Familiarity with enterprise data governance platforms (Collibra, Alation, Atlan).
•
Experience with ML platform components (SageMaker, MLflow, Feature Store).
•
Knowledge of BI/visualisation tools: Tableau, Power BI, or AWS QuickSight.
Life at Cevo
Our people are at the heart of Cevo. We’re a passionate, curious team with deep consulting expertise, working together to help organisations across Australia continuously evolve. We value collaboration, knowledge-sharing and people are curious, take ownership and care deeply about the impact of their work for customers, colleagues and the wider community.
Benefits and ways of working
•
$2,500 annual technology allowance to choose the tools and setup that work best for you.
•
Strong learning and development culture, including $2,000 per year for professional courses and two paid days off to attend courses and exams.
•
Support of the Cevo Hive Mind – a collaborative team that helps each other succeed.
•
We reward and recognise achievements and contributions.
•
An exciting start-up vibe, with enterprise-level projects and customers.
Additional information
Legal
•
We are an equal opportunity employer and welcome all applications, particularly from underrepresented groups.
•
At this stage, we can only consider candidates with unrestricted local working rights.
•
We don’t require assistance from recruitment agencies.