Lead Consultant – Data Intelligence

Posted 18 Days Ago
Be an Early Applicant
2 Locations
Hybrid
Senior level
Artificial Intelligence • Cloud • Information Technology • Consulting
The Role
Lead technical design and delivery of scalable AWS-based data platforms, oversee Databricks/Snowflake solutions, enforce engineering best practices (CI/CD, testing), drive data modelling, transformation (dbt, PySpark, SQL), governance and streaming architectures, mentor teams, and support pre-sales and platform/tooling decisions.
Summary Generated by Built In
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 
  • 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. 

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 
  • 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. 

Skills Required

  • 7-10+ years in data engineering, data architecture, or analytics roles
  • At least 3 years in a consulting or professional services environment
  • Proven track record of leading complex data platform deliveries end-to-end
  • 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
  • Commercial awareness including managing budgets and writing proposals
  • Excellent written and verbal communication; confident presenting to technical and executive audiences
  • Experience mentoring or leading small technical teams in a delivery context
  • Unrestricted local working rights (candidates must be authorized to work locally)
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The Company
Year Founded: 2015

What We Do

Cevo is a technology consultancy that helps organizations build lasting capabilities in cloud, data, and AI. They focus on modernizing platforms, automating delivery, and empowering teams to innovate continuously. By embedding AI into their delivery processes, they help clients move from pilots to production-ready systems, ensuring that transformation becomes a habit rather than a one-off project.

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