- Cevo Services
- Sydney, NSW
- Full-Time
- 42 days ago
Principal Consultant – Data Intelligence.
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Principal Consultant – Data Intelligence: our view in 3 lines...
- The Role:This role is for a principal data consulting specialist who designs and advises on cloud data platforms for enterprise clients.
- The Person:The person will architect cloud data platforms, lead solution design and technical governance, set engineering and data governance standards, oversee transformation workstreams, and support presales and client presentations.
- Requirements:The ideal candidate has 7–10+ years in data engineering, data architecture, or analytics roles, with strong AWS expertise, Databricks and/or Snowflake experience, Python and/or Scala, expert-level SQL, and dbt.
About the role
Who are you?
As a Principal Consultant - Data Intelligence at Cevo, you'll need a combination of technical skills, strategic thinking, and effective communication.
What You'll Do:
- 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
- Taking a leadership role in presales (EOI, RFI, RFP) activities, presenting solutions to our clients and answering questions in a pre sales environment
What You'll Bring:
- 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) and/or Snowflake (Snowpark, performance tuning, data sharing).
- 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.
- Demonstrable experience engaging senior stakeholders (Director/VP/C-suite) and translating business strategy into data solutions.
- Strong commercial awareness: ability 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.
- Previous Consulting experience within enterprise environments including pre sales
Desirable Skills & Certifications
· AWS Certified Data Engineer – Associate or Professional, or AWS Solutions Architect – Professional.
· Databricks Certified Professional Data Engineer or Solutions Architect.
· SnowPro Advanced: Architect or Data Engineer certification.
· 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.
