We are looking for a skilled Data Architect/Engineer with strong expertise in AWS and data lake solutions. If you’re passionate about building scalable data platforms, this role is for you. Your responsibilities will include:
Architect & Design: Build scalable and efficient data solutions using AWS services like Glue, Redshift, S3, Kinesis (Apache Kafka), DynamoDB, Lambda, Glue Streaming ETL, and EMR.
Real-Time Data Integration: Integrate real-time data from multiple Siemens orgs into our central data lake.
Data Lake Management: Design and manage large-scale data lakes using S3, Glue, and Lake Formation.
Data Transformation: Apply transformations to ensure high-quality, analysis-ready data.
Snowflake Integration: Build and manage pipelines for Snowflake, using Iceberg tables for best performance and flexibility.
Performance Tuning: Optimize pipelines for speed, scalability, and cost-effectiveness.
Security & Compliance: Ensure all data solutions meet security standards and compliance guidelines.
Team Collaboration: Work closely with data engineers, scientists, and app developers to deliver full-stack data solutions.
Monitoring & Troubleshooting: Set up monitoring tools and quickly resolve pipeline issues when needed.
You’d describe yourself as:
Experience: 3+ years of experience in data engineering or cloud solutioning, with a focus on AWS services.
Technical Skills: Proficiency in AWS services such as AWS API, AWS Glue, Amazon Redshift, S3, Apache Kafka and Lake Formation. Experience with real-time data processing and streaming architectures.
Big Data Querying Tools: Solid understanding of big data querying tools (e.g., Hive, PySpark).
Programming: Strong programming skills in languages such as Python, Java, or Scala for building and maintaining scalable systems.
Problem-Solving: Excellent problem-solving skills and the ability to troubleshoot complex issues.
Communication: Strong communication skills, with the ability to work effectively with both technical and non-technical stakeholders.