[Hiring] Senior Data Engineer @USEReady Technology

Role Description

You will own an Azure data platform end to end as the technical lead for a client engagement. You will design new sources and data products, lead data governance and cataloguing on Microsoft Purview, and keep the platform secure, fast and cost-efficient.

• Own the end-to-end design: ADF orchestration, ADLS Gen2 layout, Synapse Medallion layers and Power BI semantic models.
• Onboard new source systems: API review, Key Vault secret, linked service, Bronze tables, parameterised incremental logic, Silver procedures and Gold views.
• Design metadata-driven, reusable ADF frameworks: parent-child pipelines, watermark and CDC-style loads, alerting.
• Model Gold data products for HR, payroll and finance analytics: attrition, profitability, headcount, budget versus actual, FinOps.
• Tune Synapse Dedicated SQL Pool: distribution keys, CCI, statistics, workload management, DWU scaling and pause schedules.
• Lead the data quality framework: agree DQ rules with business owners and take DQ reporting live.
• Lead the Microsoft Purview rollout: Data Map scans of ADLS, Synapse and Power BI; ADF lineage; governance domains and data products in Unified Catalog; business glossary; classifications and sensitivity labels for PII; data quality and health in Purview.
• Set up catalog operating practices: data owners and stewards, glossary approval workflows, access policies and onboarding standards for new assets.
• Own security and access: Key Vault secret rotation, Managed Identity, Azure RBAC, least-privilege access to PII and payroll data, Power BI RLS where needed.
• Drive FinOps: track Azure spend through Cost Management exports and recommend savings.
• Prepare curated Gold data for AI and LLM analytics use cases with the right governance.
• Run requirements workshops and UAT with client business and IT stakeholders; turn manual reporting into dashboards.
• Set standards for CI/CD (GitHub, ADF / Synapse deployment across environments), code review, runbooks and documentation.
• Review code and mentor junior team members.

Qualifications

• 5–7 years in data engineering, with 3+ years delivering on the Azure data stack.
• Expert Azure Data Factory: complex orchestration, REST sources with token or session auth, pagination, error handling, metadata-driven design.
• Deep Azure Synapse Dedicated SQL Pool: MPP design, distribution and indexing strategy, performance tuning, cost control.
• Advanced T-SQL: stored-procedure frameworks, SCD Type 1/2, incremental and MERGE patterns, query-plan analysis.
• Data modelling: Medallion architecture and Kimball dimensional modelling.
• Power BI: semantic model design, advanced DAX, performance tuning, workspace and refresh management, RLS.
• Hands-on Microsoft Purview: Data Map, scanning, Unified Catalog, glossary, classifications and lineage.
• Data governance fundamentals: ownership and stewardship, metadata management, PII classification.
• Azure security: Key Vault, Managed Identity, RBAC, network basics.
• CI/CD with Git (GitHub or Azure DevOps) for ADF and Synapse.
• Has led client-facing delivery: requirements, estimates, UAT and status reporting with US stakeholders.

Requirements

• Microsoft Fabric (Lakehouse, Warehouse, Data Factory) for future migration paths.
• Python / PySpark and Spark on Synapse or Databricks.
• Azure Cost Management and FinOps practice.
• HR, payroll or finance data; CRM and ERP API integrations.
• GenAI / LLM integration on curated data.
• Certification: DP-203 / DP-700, DP-600, PL-300, AZ-305, or SC-400 / Purview-related.

What we look for

• Owns outcomes for the engagement, not just tickets.
• Explains technical trade-offs to business and IT leaders in plain terms.
• Pushes for early stakeholder alignment and firm UAT timelines.