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Contract - Senior Azure Data Engineer
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Senior/Lead Azure Data Engineer (Contract — 3 Months)
Location
: Remote (U. S. ), core overlap with CSTEngagement:Contract only (C2C) — no C2H for this roleStart: Immediate | Duration: 3 months (extension possible)Comp: Competitive hourly rate (DOE)About SmartbridgeSmartbridge 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 OpportunityOur 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) Experience8–12+ 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 HaveDesigned and implemented robust data validation procedures to verify the completeness of data transfers, ensuring all records were successfully migrated and proactively triggering alerts in cases of discrepancies. Experience with working with large SQL tables (100 million rows)IaC (Bicep/Terraform) for data resources. Event-driven integration (Service Bus/Event Grid, CDC tooling). Certs: DP-203 or AZ-204 are a plus.
Location
: Remote (U. S. ), core overlap with CSTEngagement:Contract only (C2C) — no C2H for this roleStart: Immediate | Duration: 3 months (extension possible)Comp: Competitive hourly rate (DOE)About SmartbridgeSmartbridge 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 OpportunityOur 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) Experience8–12+ 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 HaveDesigned and implemented robust data validation procedures to verify the completeness of data transfers, ensuring all records were successfully migrated and proactively triggering alerts in cases of discrepancies. Experience with working with large SQL tables (100 million rows)IaC (Bicep/Terraform) for data resources. Event-driven integration (Service Bus/Event Grid, CDC tooling). Certs: DP-203 or AZ-204 are a plus.
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