Data & BI Engineer

About the Job
We are looking for a
Data & BI Engineer
to join our team. This hybrid role covers the design, build, and maintenance of data pipelines, databases, and business intelligence solutions that power analytics, reporting, and AI-driven applications. You will be responsible for end-to-end delivery — from ingestion and modelling to database administration and BI dashboards — ensuring secure, scalable, and high-quality data services across Azure, AWS and hybrid environments.
You’ll collaborate closely with business analysts, product owners, BI developers and stakeholders to understand requirements and translate them into robust, actionable data and BI solutions. This is a hands-on engineering and DBA role that requires strong technical expertise and excellent communication.
About the Opportunity
As a Data & BI Engineer at Deeeplabs, you will:
Data Engineering & Pipelines
Design, develop, and maintain ETL/ELT processes and data pipelines across on-premise, cloud, and hybrid environments (Azure Data Services, Databricks, SQL Server, AWS Data Services).
Integrate, transform, and cleanse data from multiple sources to create reliable datasets for analytics, dashboards, and AI/ML workloads.
Build and optimise relational and semantic data models to support BI tools such as Power BI and downstream analytics.
Implement and manage data security, including row-level security and compliance with organisational standards.
Database Administration (DBA)
Administer, configure, and maintain databases across Microsoft SQL Server, Oracle, Azure SQL, AWS RDS/Redshift, and other database services.
Monitor database performance, perform tuning and indexing, and ensure robust backup and recovery procedures.
Manage database security, user access, and auditing to comply with regulatory and organisational policies.
Plan and execute database upgrades, migrations, and patching with minimal downtime.
Business Intelligence (BI)
Design, develop, and maintain interactive dashboards, KPI scorecards, and visual reports in Power BI to deliver clear, actionable insights.
Optimise data models and measures (DAX) for high-performance reporting.
Collaborate with business analysts and stakeholders to translate business requirements into functional BI solutions.
Continuously improve and enhance existing BI systems based on evolving business needs and data sources.
Collaboration & Support
Work closely with cross-functional teams to test, deploy, and maintain data and BI solutions.
Monitor and troubleshoot production data workflows, databases, and BI reports for performance, access, and data accuracy, ensuring timely resolution.
Produce clear technical documentation (data model descriptions, ETL flow diagrams, data dictionaries, backup/recovery procedures, reporting methodology) to support ongoing knowledge sharing.
About You
The Essentials
Bachelor’s degree in Computer Science, Statistics, Information Systems, or a related field.
4+ years’ experience in data engineering, data warehousing, or business intelligence development.
Strong SQL knowledge and experience with databases such as SQL Server, Oracle, Azure SQL, AWS RDS/Redshift.
Proven experience building ETL/ELT pipelines and data models in Azure Synapse, Databricks, AWS Glue or similar platforms.
Familiarity with Microsoft BI stack (Power BI, SSAS, SSRS, SSIS) and external tools (DAX Studio, Tabular Editor, ALM Toolkit).
Understanding of data warehousing concepts, semantic model design, BI development lifecycles, and performance tuning.
Experience with database administration, including performance tuning, backup/recovery, and security management.
Knowledge of orchestration tools (Power Automate, UC4 optional) and scripting (PowerShell, shell scripting optional).
Exposure to Microsoft ecosystem tools such as SSMS, SharePoint, and Azure DevOps.
Strong English communication skills, both written and verbal.
The Attributes
Excellent communication and stakeholder-management skills to translate business needs into technical solutions.
Exceptional analytical and problem-solving skills to convert data into actionable insights.
Ability to work in an agile, fast-moving environment with continual development and improvement.
Comprehensive understanding of data modelling, administration, and visualisation.
Awareness of emerging BI, data, and AI technologies and how they integrate into modern data platforms.
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