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Zubeir Mohd - Senior Data Engineer

[email protected]

Location: Remote, Remote, USA

Relocation:

Visa: GC

Senior Data Engineer with 13+ years of experience designing, developing, and supporting enterprise data platforms across healthcare, insurance, banking, government, and consulting domains. Strong experience building scalable batch and streaming data pipelines using PySpark, Spark SQL, Scala, SQL, Azure Databricks, AWS EMR, AWS Glue, and Hadoop ecosystem tools. Hands-on experience with multi-cloud data engineering across Azure and AWS, including Azure Data Factory, ADLS Gen2, Azure Databricks, AWS S3, EMR, Glue, Lambda, and Redshift. Experienced in designing enterprise-scale medallion architecture and cloud-native lakehouse solutions using Azure Databricks, Delta Lake, and PySpark. Strong expertise in batch and near real-time data processing, large-scale data transformation, performance optimization, and production-grade ETL orchestration. Hands-on experience supporting enterprise analytics, operational reporting, regulatory reporting, and data governance initiatives across cloud and big data ecosystems. Experienced in healthcare payer data engineering with claims, member eligibility, provider, pharmacy, encounter, care-management, actuarial, and reference datasets. Skilled in insurance data platforms involving policy, claims, billing, underwriting, customer, agency, quote, premium, and loss-history data integration. Developed banking data pipelines supporting account, customer, transaction, fraud, AML, reconciliation, and regulatory reporting use cases. Proficient in designing curated data layers, enterprise data warehouses, operational data stores, data marts, dimensional models, star schemas, and reporting-ready datasets. Skilled in Spark performance tuning using partitioning, broadcast joins, caching, file compaction, memory tuning, shuffle optimization, and efficient Parquet/ORC storage. Strong SQL development experience with T-SQL, PL/SQL, HiveQL, Spark SQL, stored procedures, views, triggers, indexes, functions, and query tuning. Implemented data quality frameworks for schema validation, duplicate detection, null handling, reconciliation, record counts, business-rule checks, and audit logging. Experienced with orchestration, deployment, and production support using Azure Data Factory, Databricks Workflows, Airflow, Oozie, Jenkins, Azure DevOps, Git, and Jira. Collaborative Agile team member with experience in requirements analysis, source-to-target mapping, technical documentation, code reviews, incident triage, and stakeholder communication. Experienced supporting enterprise data governance, audit compliance, data lineage tracking, and secure cloud-based analytics platforms. Keywords: sthree procedural language