Marsh McLennan
Marsh McLennan
Marsh McLennan जोखिम, रणनीति और लोगों से संबंधित सलाहकारी सेवाओं के क्षेत्र में काम करने वाली एक वैश्विक पेशेवर सेवा कंपनी है। इसके व्यवसायों में Marsh शामिल है, जो बीमा ब्रोकरेज और जोखिम प्रबंधन सेवाएं प्रदान करता है; Guy Carpenter, जो पुनर्बीमा और पूंजी रणनीतियों पर केंद्रित है; Mercer, जो स्वास्थ्य, संपत्ति और करियर परामर्श में ग्राहकों की सहायता करता है; तथा Oliver Wyman, जो रणनीति, अर्थशास्त्र और ब्रांड परामर्श में विशेषज्ञता रखता है। दुनिया भर में 85,000 से अधिक कर्मचारियों के साथ, Marsh McLennan वित्त, परामर्श, मार्केटिंग और संबंधित पेशेवर सेवाओं में विशेषज्ञता को एक साथ लाता है। कंपनी में भर्ती के अवसर इसके चारों व्यवसायों में ग्राहक सलाह, जोखिम विश्लेषण, व्यावसायिक रणनीति, परामर्श और संचालन टीमों को सहयोग देने वाली भूमिकाओं तक फैले हुए हैं।

Manager, Data Engineering - Pune (Hybrid)

Lead data engineering initiatives for Marsh McLennan’s global risk and consulting business. Build scalable Databricks, PySpark, SQL, Delta Lake, and Lakehouse solutions for governed analytics.

विवरण

  • Design and deliver scalable pipelines on the Databricks Lakehouse platform
  • Create and maintain data products based on Medallion Architecture
  • Develop pipelines for data ingestion, transformation, and consumption
  • Build business-ready Gold-layer datasets for reporting and analytics
  • Manage Delta Lake tables and related data assets
  • Implement incremental processing with Merge, Upsert, and CDC patterns
  • Improve Delta table performance through partitioning, compaction, and tuning
  • Assess legacy data flows and SQL, then convert them into efficient PySpark pipelines
  • Record transformation rules and migration strategies
  • Develop scalable PySpark applications in Databricks
  • Create reusable engineering frameworks and components
  • Tune Spark workloads and review execution plans
  • Establish data quality checks, reconciliation procedures, and validation frameworks
  • Write complex SQL, stored procedures, and efficient transformation logic
  • Use SQL for data analysis, profiling, and issue resolution
  • Improve query performance and data models for large-scale datasets
  • Support lineage, metadata, governance, CI/CD, and deployment automation
  • Partner with data architects, business stakeholders, analysts, and platform teams

आवश्यकताएँ

  • Demonstrated hands-on expertise with Databricks and Spark-based data engineering
  • Experience applying Medallion Architecture across Bronze, Silver, and Gold layers
  • Background designing and operating Delta Lake solutions
  • Solid understanding of Lakehouse Architecture concepts
  • Experience building scalable pipelines for enterprise analytics platforms
  • Knowledge of data quality, lineage, governance, and observability practices
  • Experience with Informatica is an advantage
  • Cloud engineering experience, preferably with AWS
  • Practical expertise in Databricks, PySpark, SQL, Delta Lake, Medallion Architecture, data modeling, and distributed processing at scale

लाभ

  • Opportunities for professional growth and development
  • Engaging work with supportive leadership
  • Inclusive and energetic workplace culture
  • Flexible working environment
  • Multiple career development paths
  • Benefits and rewards focused on employee well-being
  • Option to work remotely
  • Office-based collaboration, relationship building, and professional development opportunities

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