Contract - Senior Azure Data Engineer

Smartbridge • Houston, TX

3d • Remote

About The Position

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.

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.

Requirements

• 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 Haves

• Designed 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.

Responsibilities

• 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).
• 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.
• Physical/semantic modeling, partitioning, columnstore strategies, statistics management, query plan analysis, index design, concurrency & transaction isolation, workload management.
• SLA/SLO definitions, Azure Monitor / Log Analytics / App Insights dashboards and alerts; error handling, retries/backoff, idempotency, CDC and schema drift strategies.
• RBAC, Key Vault, managed identities, private endpoints/VNet, data masking patterns; document data contracts and access patterns.
• Code reviews, PR discipline, mentoring, and crisp documentation/runbooks for client handoff.

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 51-100 employees