Data Engineer AWS, Python & Data Pipelines - 206022

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.