Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.
Job Overview
Assignment Description
We are looking for a Data Engineer to design, build, test, deploy and operate secure and reliable data pipelines and engineering services on AWS.
This is a hands-on software and data engineering role focused on production code, cloud infrastructure, automation and service reliability — not data analysis or dashboard development.
You will work within a cross-functional engineering team, building data ingestion, processing and integration services that support business applications, credit operations, reporting and AI workloads.
What You Will Work On
- Build and maintain production data pipelines using Python, Spark, APIs and Kafka.
- Develop batch and streaming data ingestion services and reusable components.
- Handle schema changes, incremental loads, failures, retries and data reprocessing.
- Provision and configure AWS infrastructure using Terraform, including S3, IAM and EKS-related workloads.
- Implement automated testing, CI/CD, data validation and reconciliation checks.
- Monitor production pipelines, investigate incidents and improve service reliability.
- Maintain alerts, runbooks and recovery procedures.
- Apply security controls such as least-privilege access, encryption and secrets management.
- Optimise pipeline performance, resource usage and cloud costs.
- Document technical solutions, interfaces, dependencies and data lineage.
- Use approved AI-assisted engineering tools responsibly.
What You Bring
- Demonstrated experience building, deploying and supporting production data pipelines or data-platform services.
- Practical experience with Python and AWS.
- Strong software engineering skills, including Git, code reviews, automated testing and CI/CD.
- Experience with Spark, Kafka and API-based data ingestion.
- Knowledge of AWS services, including S3, IAM, encryption, logging and networking.
- Experience with Terraform and infrastructure automation.
- Understanding of Kubernetes/EKS and containerised workloads where required.
- Experience with Airflow orchestration and production monitoring.
- Good knowledge of SQL, data schemas, file formats and technical data models.
- Understanding of data quality, observability, recovery and performance optimisation.
- Fluent English and strong technical communication skills.
- Degree in Computer Science, Engineering or a related discipline, or equivalent practical experience.
Meritorious
- Banking and financial data experience.
- Relevant AWS certifications.
- Experience with legacy data migrations.
- Experience with dbt.
- Experience with large-scale batch and streaming data platforms.