Senior Data Engineer with AWS (All genders)

Description

The team is a global group of experts at a company that combines software, data, AI and human expertise to build digital products, services and operating models with measurable business impact.

The company has about 2,500 experts working across its international teams, helping to build, run and scale intelligence across the full value chain.

The workplace puts people and genuine human connections first, with a supportive, inclusive culture and a hybrid setup that offers a high degree of flexibility.

Responsibilities

• Design, build and maintain scalable batch and real-time data pipelines that handle structured, semi-structured and unstructured data, using AWS-native services and distributed processing frameworks.
• Architect and implement cloud-native data platforms on AWS that support efficient ingestion, transformation, storage and analytics at scale.
• Use AWS services such as Amazon S3, AWS Glue, Amazon Redshift, Amazon EMR, AWS Lambda, Amazon Kinesis and DynamoDB to build robust, cost-efficient data solutions.
• Work on fast-moving digital transformation projects for global customers, delivering data-driven solutions with measurable business value.
• Collaborate with Data Scientists, Data Analysts, Product Teams and Software Engineers to turn data requirements into scalable technical solutions.
• Evaluate and adopt new technologies, frameworks and practices in data engineering to improve platform performance, reliability and maintainability.
• Provide technical leadership in the team by mentoring colleagues, sharing your expertise and helping grow the data engineering capability.
• Write and maintain documentation, architecture diagrams and operational practices for data platforms and pipelines.

Requirements

• Over 8 years of hands-on experience in data engineering, building and running large-scale data platforms and pipelines in the cloud.
• Strong Python and SQL skills, with extensive use of Spark, PySpark, Spark SQL or other distributed processing frameworks.
• Proven experience designing and delivering end-to-end data solutions on AWS.
• Strong hands-on experience with Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, Amazon EMR, Amazon RDS, Amazon DynamoDB, AWS IAM, Amazon VPC and Amazon CloudWatch.
• Experience building modern ETL/ELT frameworks and data integration across multiple source systems.
• Solid grasp of data modeling, data warehousing, dimensional modeling and data architecture.
• Experience with orchestration and workflow tools such as AWS Step Functions, Apache Airflow or AWS Managed Workflows for Apache Airflow (MWAA).
• Strong experience in Unix/Linux environments and Bash scripting for automation and operational support.
• Experience applying security, governance and access control practices in AWS environments.
• Excellent communication skills and experience working in cross-functional Agile teams.
• Experience with real-time and event-driven architectures using Amazon Kinesis, Apache Kafka, Amazon MSK or similar streaming technologies.
• Hands-on experience with data lake and lakehouse architectures, including AWS Lake Formation, Apache Iceberg, Delta Lake or Apache Hudi.
• Experience with Infrastructure as Code using Terraform, AWS CloudFormation or AWS CDK.
• Experience building CI/CD pipelines with GitHub Actions, GitLab CI/CD, Jenkins or AWS CodePipeline.
• Knowledge of containers and orchestration with Docker, Amazon ECS, Amazon EKS and Kubernetes.
• Familiarity with monitoring and observability tools such as CloudWatch, Grafana, Prometheus and Datadog.
• AWS certifications such as AWS Certified Data Engineer, Associate, AWS Certified Solutions Architect, Associate or Professional, or AWS Certified Developer, Associate.
• Experience in consulting environments and customer-facing projects.
• Experience working in Agile or Scrum delivery environments.

Conditions

Hybrid work model with a high degree of flexibility.

Equal opportunity: every application is welcomed and considered equally, and any discrimination or harassment is opposed.

Benefits

• Training programs, free language courses, competence centers and an active tech community for professional and personal growth.
• Hybrid work, workation, flexible hours, parental support and sabbaticals.
• Sustainability Hub, diverse communities, a Diversity Taskforce and after-work activities.
• Public transport tickets, job bikes, exclusive Volkswagen employee conditions when leasing or buying a vehicle, health offers, supplementary insurance, a pension plan and various discounts.