Senior Data Engineer

dentsu Austria

Data Engineer designing and building big data architectures for cloud-based data lake houses at Merkle. Collaborating with international teams on data projects for leading brands.

Posted 7/7/2026full-timePrague • CzechiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing data ingestion and processing pipelines using public cloud services, with a strong focus on big data architectures and machine learning model deployment. Proficient in utilizing CI/CD tools and Agile methodologies to enhance data infrastructure and support business intelligence initiatives.

Highest-signal resume keywords

Advanced Python ProgrammingBig Data TechnologiesData Ingestion and ProcessingCI/CD Automation ToolsRelational and NoSQL Databases

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData ProcessingBig Data ArchitectureMachine Learning DeploymentData Pipeline DevelopmentData TransformationStreaming TechnologyETL ServicesData AnalysisInfrastructure as Code

Soft Skills

Good Communication SkillsOrganizational SkillsAdaptabilityResponsibility

Tools & Technologies

AzureAWSGCPDatabricksSnowflakeKafkaAirflowJiraConfluenceAzure DevOps

Industry Keywords

Data LakeLambda ArchitectureStream ProcessingBusiness IntelligenceData Warehouse

Tech Stack

Tools & technologies

AirflowAWSAzureBigQueryCloudDynamoDBElasticSearchETLGoogle Cloud PlatformJavaJenkinsKafkaMongoDBNoSQLPostgresPythonRedisScalaSQL

About the role

Key responsibilities & impact

Design and implement data ingestion and processing of various data sources using public cloud services.
Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs, like optimizing existing data delivery, re-designing infrastructure for greater scalability, etc.
Collaborate with Business Intelligence consultants and assemble large and complex data sets that meet functional and non-functional business requirements for data lakehouse.
Support machine learning teams in deployment and optimization of AI / Machine Learning models and other data algorithms.
Develop data pipelines to provide actionable insights into marketing automation, customer acquisition and other key businesses areas.
Use infrastructure as a code and CI/CD tools to automate release automation pipelines.
Document data pipelines and logic in a structured manner using Confluence, plan your activities using Agile methodology in Jira.
Support pre-sales by proposing technical solutions and accurate effort estimation.

Requirements

What you’ll need

Experience in building and productionizing big data architectures, pipelines and data sets.
Understanding data concepts and patterns of big data, data lake, lambda architecture, stream processing, DWH, and BI.
3-7 years of experience in a Data Engineer role, who has attained experience using the following software/tools: Advanced Python programming.
Experience with other object-oriented / functional / scripting languages like Bash, Scala, Java, R, PowerShell etc.
Data related services from Azure, AWS, and GCP public clouds.
Big data technologies like Databricks, Fabricm, AWS Glue, Snowflake, Dataproc, BigQuery, etc.
Extensive working experience with relational databases like MS SQL, Postgres, Aurora DB and NoSQL databases like DynamoDB, MongoDB, Elasticsearch, Redis, etc.
Streaming technology services like Kafka, Event Hubs, and Kinesis, etc.
Orchestration, compute, and ETL services like dbt, Airflow, Cloud Composer, AWS Step Functions, AWS Lambda, Azure Functions etc.
Strong analytic skills related to working with structured and unstructured datasets.
Build processes supporting data transformation, data structures, metadata, dependency and workload management.
Experience in setting up and using CI/CD automation tools like Azure DevOps, GitHub actions, Jenkins, etc.
Person who is precise, well organized, has good communication skills, can adapt to changing circumstances and is not afraid of responsibility for his / her work will do great in this role.

Benefits

Comp & perks

Flexibility & Balance: Enjoy hybrid work models, adaptable hours, and home office options.
Inclusive & Supportive Culture: We celebrate diversity and foster a respectful workplace where every team member’s unique perspective is valued, and everyone is welcome.
Well-balanced reward package: We offer competitive salaries, volunteer days, wellness days, modern offices, and a multi-cultural environment that fosters creativity and innovation.
Innovation-Driven Work: Contribute to projects that are reshaping industries and driving transformation with next-generation technologies and strategies.
Purpose-Driven Culture: Be part of an organization that fosters sustainable growth for brands, people, and society—where every contribution makes a meaningful impact.
Growth Opportunities: Expand your skills through training, mentorship, and data-driven projects that reshape customer experience and business outcomes.