Data Engineers

Key Responsibility

• Design and build scalable data platforms using modern cloud-native and Lakehouse architectures

• Develop and optimise data pipelines using Python, SQL, and tools such as Azure Data Factory, AWS Glue, Google Cloud Dataflow, Databricks, and dbt

• Modernise legacy data environments, migrating from on-premises solutions to cloud-native platforms such as Microsoft Fabric, Azure Synapse Analytics, AWS Redshift, Google Big Query, or Databricks

• Engage with clients to conceptualize data solutions aligned to their business strategy

• Support our sales team with pre-sales activities, proof-of-concept deliveries, and technical proposals

• Provide technical guidance and mentorship to junior and intermediate consultants

• Lead technical reviews and contribute to consultants' growth plans

• Identify opportunities to automate manual processes, optimise data delivery, and improve infrastructure scalability

• Work with stakeholders, including executive, product, and analytics teams, to address data infrastructure needs

• Drive knowledge sharing through technical blogs, internal forums, and workshops

• Balance billable project work with team support responsibilities

3-5 years' experience

• 3-5 years of hands-on experience in data engineering.

• Strong proficiency in Python and/or SQL , including query optimisation.

• Experience working with both relational and non-relational databases.

• Experience designing and building data pipelines and data models.

• Understanding and practical experience with lakehouse architectures , including the medallion pattern.

• Practical experience with at least one major cloud platform, including:

  • Microsoft Azure

  • AWS

  • Google Cloud Platform (GCP)

• Familiarity with:

  • Databricks

  • Snowflake

  • Delta Lake

  • Py Spark

• Understanding of data transformation frameworks such as dbt .

• Experience with version control using Git .

• Understanding of CI/CD practices for data workflows.

• Strong analytical and problem-solving skills.

• Ability to perform root-cause analysis on complex data issues.

• Good communication and stakeholder engagement skills.

6-8+ years' experience

• 6-8+ years of hands-on experience in data engineering.

• All intermediate-level technical requirements, together with demonstrable experience in:

  • Leading end-to-end data platform delivery.

  • Architecting enterprise-grade lakehouse environments.

  • Implementing data mesh patterns.

  • Infrastructure-as-code using tools such as Terraform, Bicep, AWS CDK or Pulumi.

  • Dev Ops and CI/CD pipelines.

  • Working effectively with cross-functional teams in a dynamic consulting environment.

  • Mentoring junior engineers.

  • Contributing to technical strategy and solution direction.

• Bachelor's degree in:

  • Computer Science

  • Information Systems

  • Information Technology

  • or a related field.

• Master's degree in a relevant field is advantageous.

One or more of the following certifications would be advantageous:

• Microsoft Fabric Data Engineer Associate

• Microsoft Azure Data Engineer Associate

• Databricks Certified Data Engineer Associate

• Google Professional Data Engineer

• AWS Certified Data Engineer
  - Associate

• Databricks Certified Data Engineer Professional

• Python

• Py Spark

• SQL

• dbt

• Microsoft Fabric Lake houses

• Fabric Pipelines

• Fabric Semantic Models

• Direct Lake

• Azure Data Factory

• Azure Data Lake Storage Gen2

• Azure Synapse Analytics

• Azure Databricks

• Azure Event Hubs

• Big Query

• Cloud Storage

• Dataflow

• Dataproc

• Pub/Sub

• Amazon S3

• AWS Glue

• Amazon Redshift

• Amazon EMR

• Amazon Kinesis

• Databricks

• Delta Lake

• Unity Catalog

• MLflow

• Databricks Workflows

• Azure SQL

• Azure Cosmos DB

• PostgreSQL

• Snowflake

• Big Query

• Amazon Redshift

• Git

• Azure Dev Ops

• Git Hub Actions

• Terraform

• Bicep

• AWS CDK

• CI/CD pipelines

• Azure Event Hubs

• Azure Stream Analytics

• Apache Kafka

• Amazon Kinesis

• Google Pub/Sub

• Microsoft Power BI

• Microsoft Fabric Real-Time Dashboards

• Looker / Looker Studio

• Amazon Quick Sight