Lead Azure Data Engineer

#hiring #Lead #Azure #DataEngineer #Pyspark #ADF #Synapse #ADLS #AzureDevops #RBAC #Remote #CST #USCitizen #GreenCard  Please let me know if you are interested in the position Title: Senior/Lead Azure Data Engineer Location: Remote (U.S.), core overlap with CST Duration: 6-12Months MOI: Phone/Skype/Teams VISA: USC GC Only     ---------------------------JOB DESCRIPTION---------------------------   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.   Thanks and Regards Sarfaraz Khan US IT Recruiter Email: [Upgrade to PRO to see contact] #