We are seeking an all‑round engineer who blends modern data engineering with automation and Microsoft 365 expertise. You will design and run reliable data pipelines (SQL Server/PostgreSQL → Azure), build and govern our data products, automate business workflows (Power Automate/Python), produce Power BI dashboards, and support AI/ML initiatives (Azure ML, Azure OpenAI). You may also contribute to Microsoft 365 records‑management workflows (SharePoint Online, Purview, Security \& Compliance).
You will work closely with business teams, vendors, and IT to translate requirements into secure, scalable, and maintainable solutions.
Candidates with suitable qualifications and experience will be considered for a senior position.
Roles \& Responsibilities
Data Engineering \& Platform
Design, build, and operate ETL/ELT pipelines for batch/near‑real‑time workloads across SQL Server, PostgreSQL, and Azure services.
Model data warehouses; implement data quality checks, lineage, and documentation.
Integrate third‑party systems via REST/web APIs.
Version, test, and release data code (SQL, Python, Power Automate, scripts) with CI/CD, instrument pipelines for observability and cost.
Analytics \& Automation
Build Power BI models and reports (DAX, Power Query), enforce governance (certified datasets, RLS), and optimize refresh.
Automate processes using Power Automate and Python (RPA where appropriate); schedule and monitor jobs.
AI/ML \& MLOps
Prepare features/datasets and partner with business analysts on Azure ML experiments and deployments.
Use
Azure OpenAI
responsibly to solve business use cases.
Microsoft 365 Records \& Compliance
Develop SharePoint Online workflows for records transactions; integrate with metadata/labels.
Configure/operate retention labels, policies, and Microsoft Purview / M365 Security \& Compliance features alongside IT Security.
Work Practices
Translate ambiguous business needs into technical designs and increments; create documentation and runbooks.
Collaborate with vendors and internal IT; uphold security, privacy, and regulatory requirements.
Manage multiple concurrent projects end-to-end, balancing delivery speed, quality, and security.
Required Skills \& Experience
Data modeling \& SQL.
Advanced SQL; schema design; performance tuning on relational database such as SQL Server and PostgreSQL.
Pipelines/ETL/ELT.
Hands‑on building production pipelines from multiple sources (including web APIs) with strong data quality practices; experience with developing and maintaining SSIS packages.
Programming \& Scripting.
Proficiency in Python; experience automating tasks, calling APIs, and handling files/JSON/CSV/XML.
Power BI.
Data modelling (star schemas), DAX, Power Query, RLS, incremental refresh, gateway configuration.
Automation.
Power Automate flow development and administration.
Azure data/AI.
Practical exposure to Azure services supporting data and ML (e.g., storage, compute, orchestration, Azure ML; Azure OpenAI familiarity).
Nice to Have
Experience with ADF/Synapse/Fabric orchestration; Git‑based development; unit/integration testing for data.
RPA experience beyond Power Automate; Playwright/Power Automate Desktop for UI automation (used judiciously).
Data governance tooling and BI usage analytics.
Deep SSIS package development (project/deployment model, parameters, configurations) and SSIS → ADF/Fabric migration experience.
M365 ecosystem. SharePoint Online solutioning and workflow development; awareness of Purview retention labelling and M365 Security \& Compliance.
Qualifications
Bachelor’s degree in Computer Science, Data/Information Systems, Engineering, Mathematics, or related quantitative field.
Strong analytical thinking, excellent English communication, and demonstrated self‑learning/growth mindset.
Ability to engage non‑technical stakeholders and document solutions clearly