Job description

Senior/Lead Azure Data Engineer (Contract — 3 Months) Location: Remote (U.S.), core overlap with CST Engagement: Contract only (1099/C2C) — no C2H for this role Start: Immediate | Duration: 3 months (extension possible) Comp: Competitive hourly rate (DOE) About Smartbridge Smartbridge simplifies business transformation across App Development, Automation, Data & Analytics, and Modernization. We build production systems for clients in Energy, Life Sciences, and Food & Beverage. The Opportunity Our project needs a senior/lead who can both design and build modern Azure data platforms—someone with strong coding in T-SQL and Python/PySpark, architectural judgment, and deep database chops (modeling, performance, reliability). Because this is contract-only, fit must be tight and immediate impact. What You’ll Own (Architecture + Build) • Architecture: Define the target-state Azure data architecture (ingestion, orchestration, storage zones, serving patterns), security/networking boundaries, cost/perf tradeoffs, and promotion strategy (Dev→Test→Prod). • Pipelines & Code: Implement robust ELT/ETL with ADF/Synapse Pipelines (parameters, reusable templates, CI/CD). Hands-on in T-SQL and Python/PySpark for transformations, utilities, and tests. • Database Excellence: Physical/semantic modeling, partitioning, columnstore strategies, statistics management, query plan analysis, index design, concurrency & transaction isolation, workload management. • Observability & Reliability: SLA/SLO definitions, Azure Monitor / Log Analytics / App Insights dashboards and alerts; error handling, retries/backoff, idempotency, CDC and schema drift strategies. • Security & Governance: RBAC, Key Vault, managed identities, private endpoints/VNet, data masking patterns; document data contracts and access patterns. • Leadership: Code reviews, PR discipline, mentoring, and crisp documentation/runbooks for client handoff. Must-Have (Senior-Level) Experience • 8–12+ years in data engineering (recent Azure focus). • Expert with ADF (linked services, datasets, IRs—including self-hosted), Synapse (SQL pools/serverless, pipelines), and ADLS/Blob. • T-SQL: advanced query tuning, execution plan analysis, windowing, TVFs/stored procs, temp tables vs CTE tradeoffs, cardinality estimator know-how. • Python/PySpark: production data transforms, packaging, and testing. • CI/CD: Azure DevOps or GitHub Actions (multi-stage releases, approvals, infra + data deployments). • Proven delivery of production-grade platforms at scale (TB-level data, strict SLAs). Not a fit: Primarily BI/reporting backgrounds without strong pipeline/build + DB performance experience. Nice to Have • Databricks, Delta Lake, Unity Catalog; Purview/Fabric governance concepts. • IaC (Bicep/Terraform) for data resources. • Event-driven integration (Service Bus/Event Grid, CDC tooling). • Certs: DP-203 or AZ-204 are a plus. Powered by JazzHR 7cT4um0ez9

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