Senior Data Engineer (Azure)

USEReady is a data and analytics firm that provides the strategies, tools, capability, and capacity that businesses need to turn their data into a competitive advantage.

USEReady partners with cloud and data ecosystem leaders like Tableau, Salesforce, Snowflake and Amazon Web Services, and has been named Tableau partner of the year multiple times.

Description

Role: Senior Data Engineer ·

Experience: 5–7 years

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.

What you will do

• 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.

Must have

• 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.

Good to have

• 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.