We are an emerging AI-native product-driven agile start-up under Abu Dhabi government AND we are seeking a motivated and technically versatile Data Engineer to join our team. You will play a key role in delivering data platforms pipelines and ML enablement within a Databricks on Azure environment.
As part of a stream-aligned delivery team youll work closely with Data Scientists Architects and Product Managers to build scalable high-quality data solutions for clients. Youll be empowered by a collaborative environment that values continuous learning Agile best practices and technical excellence.
Ideal candidates have strong hands-on experience in Databricks Python ADF and are comfortable in fast-paced client-facing consulting engagements.
Skills and Experience requirements 1. Technical
Databricks (or similar) e.g. Notebooks (Python SQL) Delta Lake job scheduling clusters and workspace management Unity Catalog access control awareness
Cloud data engineering ideally Azure including storage (e.g. ADLS S3 ADLS) compute and secrets management
Development languages such as Python SQL C# javascript etc. especially data ingestion cleaning and transformation
Automated testing (ideally TDD) pairing/mobbing. Trunk Based Development Continuous Deployment and Infrastructure-as-Code (Terraform)
Git and CI/CD for notebooks data pipelines and deployments
2. Integration & Data Handling
Experienced in delivering platforms for clients including file transfer APIS (REST etc.) SQL/NoSQL/graph databases JSON CSV XML Parquet etc
Data validation and profiling - assess incoming data quality. Cope with schema drift deduplication and reconciliation
Testing and monitoring pipelines: Unit tests for transformations data checks and pipeline observability
3. Working Style
Comfortable leveraging the best of lean agile and waterfall approaches. Can contribute to planning estimation and documentation but also collaborative daily re-prioritisation
Able to explain technical decisions to teammates or clients
Documents decisions and keeps stakeholders informed
Comfortable seeking support from other teams for Product Databricks Data architecture
Happy to collaborate with Data Science team on complex subsystems
Requirements
Nice-to-haves
MLflow or light MLOps experience (for the data science touchpoints)
Dbt / dagster / airflow or similar transformation tools
Understanding of security and compliance (esp. around client data)
Past experience in consulting or client-facing roles
Candidate Requirements
58 years (minimum 34 years hands-on with cloud/data engineering 12 years in Databricks/Azure and team/project leadership exposure)
Bachelors degree in Computer Science Data Engineering Software Engineering Information Systems Data Engineering
Job Type: Full-time
Benefits
Visa Insurance Yearly Flight Ticket Bonus scheme relocation logistics covered
Interviewing process consists of 2 or 3 technical/behavioral interviews
TasksAbout the RoleWe are an emerging AI-native product-driven agile start-up under Abu Dhabi government AND we are seeking a motivated and technically versatile Data Engineer to join our team. You will play a key role in delivering data platforms pipelines and ML enablement within a Databricks on A...
Tasks
About the Role
We are an emerging AI-native product-driven agile start-up under Abu Dhabi government AND we are seeking a motivated and technically versatile Data Engineer to join our team. You will play a key role in delivering data platforms pipelines and ML enablement within a Databricks on Azure environment.
As part of a stream-aligned delivery team youll work closely with Data Scientists Architects and Product Managers to build scalable high-quality data solutions for clients. Youll be empowered by a collaborative environment that values continuous learning Agile best practices and technical excellence.
Ideal candidates have strong hands-on experience in Databricks Python ADF and are comfortable in fast-paced client-facing consulting engagements.
Skills and Experience requirements 1. Technical
Databricks (or similar) e.g. Notebooks (Python SQL) Delta Lake job scheduling clusters and workspace management Unity Catalog access control awareness
Cloud data engineering ideally Azure including storage (e.g. ADLS S3 ADLS) compute and secrets management
Development languages such as Python SQL C# javascript etc. especially data ingestion cleaning and transformation
Automated testing (ideally TDD) pairing/mobbing. Trunk Based Development Continuous Deployment and Infrastructure-as-Code (Terraform)
Git and CI/CD for notebooks data pipelines and deployments
2. Integration & Data Handling
Experienced in delivering platforms for clients including file transfer APIS (REST etc.) SQL/NoSQL/graph databases JSON CSV XML Parquet etc
Data validation and profiling - assess incoming data quality. Cope with schema drift deduplication and reconciliation
Testing and monitoring pipelines: Unit tests for transformations data checks and pipeline observability
3. Working Style
Comfortable leveraging the best of lean agile and waterfall approaches. Can contribute to planning estimation and documentation but also collaborative daily re-prioritisation
Able to explain technical decisions to teammates or clients
Documents decisions and keeps stakeholders informed
Comfortable seeking support from other teams for Product Databricks Data architecture
Happy to collaborate with Data Science team on complex subsystems
Requirements
Nice-to-haves
MLflow or light MLOps experience (for the data science touchpoints)
Dbt / dagster / airflow or similar transformation tools
Understanding of security and compliance (esp. around client data)
Past experience in consulting or client-facing roles
Candidate Requirements
58 years (minimum 34 years hands-on with cloud/data engineering 12 years in Databricks/Azure and team/project leadership exposure)
Bachelors degree in Computer Science Data Engineering Software Engineering Information Systems Data Engineering
Job Type: Full-time
Benefits
Visa Insurance Yearly Flight Ticket Bonus scheme relocation logistics covered
Interviewing process consists of 2 or 3 technical/behavioral interviews