dentsu Austria
dentsu Austria
51 – 200 Angajați
ÎntreprindereMarketingMedia
dentsu Austria este divizia austriacă a grupului global Dentsu și ajută organizațiile să abordeze transformarea afacerilor, marketingul și creșterea durabilă. Activitatea sa combină cercetarea, analiza, expertiza în media și soluțiile integrate pentru a ajuta mărcile să navigheze pe piețele în schimbare și să creeze experiențe relevante. Ca parte a unei rețele internaționale, dentsu Austria reunește perspective din marketing, media și servicii pentru companii, transformând provocările complexe în oportunități practice pentru clienți, publicul lor și societate.

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.

Descriere

  • 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

Cerințe

  • 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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