dentsu Austria
dentsu Austria
51 – 200 कर्मचारी
उद्यममीडियाविपणन
dentsu Austria वैश्विक Dentsu Group की ऑस्ट्रियाई शाखा है, जो संगठनों को व्यावसायिक परिवर्तन, मार्केटिंग और सतत विकास की चुनौतियों से निपटने में मदद करती है। इसका काम अनुसंधान, विश्लेषण, मीडिया विशेषज्ञता और एकीकृत समाधानों को जोड़कर ब्रांडों को बदलते बाजारों में दिशा तय करने और सार्थक अनुभव बनाने में सहायता करता है। एक अंतरराष्ट्रीय नेटवर्क के हिस्से के रूप में, dentsu Austria मार्केटिंग, मीडिया और उद्यम सेवाओं के विभिन्न दृष्टिकोणों को एक साथ लाकर ग्राहकों, उनके दर्शकों और समाज के लिए जटिल चुनौतियों को व्यावहारिक अवसरों में बदलता है।

Senior AWS Technical Lead, Data Engineering — Pune Onsite

Lead the design and delivery of scalable AWS data platforms for enterprise clients. Build secure batch and streaming pipelines with SQL, Python, Spark, and infrastructure automation.

विवरण

  • Design AWS data engineering solutions that meet enterprise standards
  • Develop and optimize batch and streaming pipelines with AWS-native and open-source technologies
  • Create SQL transformations and Python pipelines for analytics workloads
  • Model data for scalability, performance, and cost efficiency
  • Manage data engineering work from development through production support
  • Improve performance, control costs, and plan platform capacity
  • Diagnose complex pipeline and production failures through root-cause analysis
  • Deliver solutions that satisfy security, reliability, and scalability expectations
  • Collaborate with architects, product owners, and client stakeholders
  • Convert business and analytics needs into dependable AWS data solutions
  • Provide technical estimates, implementation guidance, and trade-off analysis
  • Support solution planning and technical design reviews
  • Apply and improve coding standards, documentation, and data engineering practices
  • Take part in code reviews and continuous improvement work
  • Maintain compliance with AWS, security, and regulatory requirements

आवश्यकताएँ

  • Bring 6–10 years of professional experience
  • Demonstrate strong hands-on knowledge of AWS data services, including Amazon S3, Glue, Athena, and Redshift
  • Design cloud-native AWS data lakes and data warehouse architectures
  • Understand batch and streaming pipeline design in depth
  • Build scalable, fault-tolerant ingestion and transformation workflows
  • Use advanced SQL for transformations, aggregations, analytics, and performance tuning
  • Work with large datasets in Amazon Redshift and Athena
  • Write production-quality Python for data engineering applications
  • Create reusable ETL components, utilities, and pipelines
  • Apply data modeling, transformation, and performance optimization principles
  • Use Spark, PySpark, or comparable distributed processing frameworks
  • Handle structured, semi-structured, and unstructured data
  • Understand schema design, partitioning, and query optimization
  • Use Terraform and/or CloudFormation for infrastructure as code
  • Build and maintain CI/CD pipelines for data platforms
  • Work with containerized workloads such as Docker and ECS/EKS
  • Take ownership of solution quality, performance, and production stability
  • Communicate effectively with architects, DevOps, QA, and business stakeholders
  • Hold a bachelor's or master's degree in computer science, information systems, data engineering, or a related discipline
  • Have an AWS Data Analytics or Solutions Architect certification, with any two of the listed certifications
  • Databricks, Snowflake, or other cloud data platform certifications are advantageous
  • Be available to work either 12 PM–9 PM or 2 PM–11 PM IST

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