Senior Databricks Architect for Data Mesh & Streaming

Infosys Limited; København; Hybrid; DKK 800,000 - 1,200,000; Full time

Job summary

Infosys is seeking a Senior Databricks Architect in Copenhagen to design, build, and operate scalable data pipelines and data products. The role focuses on modern data mesh architectures, integrating legacy systems with cloud-native platforms to support analytics, reporting, and domain-owned data products.

You will work with Databricks, Spark, PySpark/SQL, and Confluent Kafka to implement batch and streaming pipelines into AWS-based data lakes, ensuring governance, security, and high data

Qualifications

• Experience with Databricks (Spark, PySpark/SQL) and data lake architectures.
• Hands-on experience with streaming technologies, especially Kafka.
• Experience integrating legacy data sources such as DB2 and SQL Server.
• Working knowledge of AWS data services, especially S3.
• Understanding of data product thinking and data mesh concepts.

Responsibilities

• Build and maintain batch and streaming data pipelines from legacy systems into an AWS-based data lake.
• Implement real-time ingestion using Confluent Kafka and land data in S3.
• Develop data transformations and analytics pipelines in Databricks using Bronze-Silver-Gold medallion architecture.
• Design and deliver high-quality, reusable data products aligned to data mesh principles.
• Ensure data quality, reliability, security, and governance across pipelines.
• Collaborate with domain and platform teams to enable self-serve analytics.

Skills

Databricks expertise

Streaming technologies

Data mesh concepts

Data quality and governance

Communication skills

Tools

Databricks

Kafka

Confluent Kafka

DB2

SQL Server

AWS S3

AWS data services

Job description

Infosys is seeking a Senior Databricks Architect in Copenhagen to design, build, and operate scalable data pipelines and data products. The role focuses on modern data mesh architectures, integrating legacy systems with cloud-native platforms to support analytics, reporting, and domain-owned data products.

You will work with Databricks, Spark, PySpark/SQL, and Confluent Kafka to implement batch and streaming pipelines into AWS-based data lakes, ensuring governance, security, and high data