dentsu Austria
dentsu Austria
51 – 200 Xodimlar
KorxonaMarketingMedia
dentsu Austria global Dentsu Group kompaniyasining Avstriyadagi bo‘linmasi bo‘lib, tashkilotlarga biznes transformatsiyasi, marketing va barqaror o‘sish masalalarini hal qilishda yordam beradi. Kompaniya brendlarga o‘zgarib borayotgan bozorlarda yo‘l topish va mazmunli tajribalar yaratishga ko‘maklashish uchun tadqiqot, tahlil, media sohasidagi tajriba hamda integratsiyalashgan yechimlarni birlashtiradi. Xalqaro tarmoqning bir qismi sifatida dentsu Austria marketing, media va korporativ xizmatlar yo‘nalishlaridagi qarashlarni jamlab, mijozlar, ularning auditoriyasi va jamiyat uchun murakkab muammolarni amaliy imkoniyatlarga aylantiradi.

Data Engineer – Pune, Onsite

Build AWS-based data platforms and ETL pipelines in Pune for Merkle. Develop SQL and Python solutions, strengthen data quality, and support analytics delivery.

Tavsif

  • Create scalable ETL and ELT pipelines on AWS
  • Develop SQL transformations and Python data pipelines for production workloads
  • Build ingestion workflows with AWS S3, Glue, and EMR
  • Design data models that support analytics while balancing performance and cost
  • Assist with deploying and running pipelines across multiple environments
  • Track pipeline performance, reliability, and data quality
  • Investigate pipeline failures and conduct root-cause analysis
  • Apply engineering practices that improve security, reliability, and scalability
  • Partner with architects and product teams to clarify technical requirements
  • Convert business and analytics needs into practical AWS data solutions
  • Support documentation, code reviews, and shared engineering standards
  • Work as an individual contributor on data pipelines, cloud engineering, and analytics enablement in a global delivery environment

Talablar

  • Bring 3 to 7 years of relevant professional experience
  • Demonstrate hands-on knowledge of AWS data services, including S3, Glue, Athena, Redshift, and EMR
  • Have experience designing cloud-native data lake and data warehouse architectures
  • Understand batch processing and have basic familiarity with streaming concepts
  • Use SQL confidently for complex queries, joins, aggregations, and transformations
  • Have worked with large datasets in Redshift or Athena
  • Use Python effectively for data engineering and ETL development
  • Experience with PySpark or Spark is advantageous
  • Understand data modeling, transformation design, and performance tuning
  • Have practical experience with distributed processing frameworks such as Spark or PySpark
  • Be comfortable working with structured and semi-structured data
  • Understand schema evolution, data quality checks, and validation logic
  • Have working knowledge of Infrastructure as Code with Terraform and/or CloudFormation
  • Bring basic experience with CI/CD pipelines for data workloads
  • Understand logging and monitoring with CloudWatch
  • Collaborate effectively with architects, DevOps, QA, and business stakeholders
  • Explain technical concepts clearly to different audiences
  • Hold a bachelor's, master's, or equivalent degree
  • An AWS Certified Solutions Architect or DevOps – Professional certification is listed
  • A Snowflake Core certification is listed

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