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.

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.

Descriere

  • 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

Cerințe

  • 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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