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.