Senior Data Engineer – Data Platform

OEC; Babsk, Kraków; On-site; PLN 200,000 - 280,000; Full time

Job summary

OEC is seeking a Senior Data Platform Engineer to join the team building our cloud-native data infrastructure on AWS. You will design and evolve a platform that serves both data producers and consumers, providing reusable, self-service capabilities for ingestion, curation, governance, access interfaces, and observability.

This is a platform engineering role focused on generic, shared infrastructure rather than one-off pipelines, with responsibilities spanning ETL templates, data contracts, CI/CD

Qualifications

• 5+ years in Data/Platform engineering with AWS focus.
• Experience with production-grade data platforms and complex data infra.
• Strong Python for pipelines, automation, and scripting.
• Familiarity with data ingestion via APIs, SFTP, or message queues.
• Experience with streaming systems like Kafka or AWS Kinesis.
• Knowledge of data quality and observability practices.

Responsibilities

• Contribute to reusable ETL templates, serverless and event-driven pipelines.
• Build self-service platform components for data producers and consumers.
• Define data contracts and pipeline configuration standards.
• Implement data lineage tracking and observability tooling.
• Develop CI/CD pipelines and infrastructure as code using Terraform.
• Shape future platform capabilities including streaming integrations and AI-assisted features.

Skills

Python

Data modeling

ETL

AWS services

Kafka / Kinesis

Observability

Terraform

Soda Core

DataZone catalog

Tools

Terraform

Datadog

Claude Code

Job description

Since the year 2000, OEC has grown globally to more than 1,000 employees with a double-digit revenue increase nearly every year. We provide a lively culture, employee rewards and recognition, and the opportunity to develop and implement innovative technology solutions.

About The Role

We’re looking for a Senior Data Platform Engineer to join the team building our cloud-native data infrastructure on AWS. You will be an active contributor to the design and evolution of a platform that serves both data producers and consumers, providing reusable, self-service capabilities for ingestion, curation, aggregation, governance, access interfaces, and observability. This is a platform engineering role: the solutions you build are generic, shared infrastructure, not one-off pipelines.

Responsibilities

• Contribute to the design and implementation of reusable ETL pipeline templates, scalable, serverless, and event-driven for processing and transforming large datasets from diverse sources
• Help build reusable, self-service platform components that abstract infrastructure complexity for data producers and consumers.
• Define and evolve standards of data contracts and pipeline configuration schemas that standardize how teams onboard to the platform.
• Implement data lineage tracking, and observability tooling to give producers and operators full visibility into platform health.
• Implement and maintain CI/CD pipelines and infrastructure as code using Terraform.
• Contribute to the technical direction of future platform capabilities, including streaming integrations, consumption interfaces, data democratization, and AI-assisted features such as failure remediation and automated contract suggestions.

You Will Be a Great Fit If You…

• Have 5+ years of professional experience as a Data Engineer or Platform Engineer with strong focus on AWS services
• Have a proven track record of contributing to production‑grade data platforms or complex data infrastructure.
• Understand data modeling and have a solid grasp of ETL best practices.
• Are proficient in Python for pipeline development, automation, and scripting.
• Are familiar with data ingestion mechanisms such as APIs, SFTP, or message queues.
• Have experience building event‑driven architectures and scalable, cloud‑native data pipelines.
• Have hands‑on experience with streaming platforms such as Kafka or AWS Kinesis.
• Implement and maintain data quality rules using Soda Core, integrate quality check results with the DataZone catalog, and define the platform's approach to quality failure handling within the pipeline execution flow.
• Are comfortable building and managing infrastructure using Terraform.
• Use observability tools to monitor logs, performance, and system health.
• Can communicate technical concepts clearly and contribute to cross‑team alignment.

Tech Stack

• Cloud AWS: S3, Iceberg, DynamoDB, RDS, Glue, Athena, Lambda, Step Functions, EventBridge, Transfer Family, SageMaker, Lake Formation, DataZone, KMS, IAM Identity Center, SES
• Languages: Python, SQL
• Infrastructure as Code: Terraform
• CI/CD: Jenkins, GitHub Actions

Nice to Have

• Experience with Datadog for cloud observability and alerting.
• Familiarity with AI‑assisted developer tools such as Claude Code or similar.