Data Ingestion Engineer — Scalable Pipelines & Data Quality

Seargin; Poland; Remote; PLN 180,000 - 280,000; Full time

Benefits offered by this job

B2B Contract

Stable and Dynamic International Firm

Engaging Projects and Latest IT

Competitive Rates

Renowned International Projects

MultiSport and Private Medical Care

Job summary

Seargin is seeking a data engineering professional to build and maintain scalable data pipelines. You will design data models with Iceberg, optimize SQL and Spark workloads, and apply automated data quality checks. The role emphasizes Python development, TDD, and AWS services integration in an international setting.

Join a team delivering complex data solutions and leverage modern tools like dbt and Airflow to ensure robust, scalable data platforms across environments.

Qualifications

• Proven experience designing and building scalable data pipelines.
• Strong Python-based data pipeline development with TDD.
• Familiarity with CI/CD, IaC, and automated testing.
• Expertise in data modeling, schema design and scalable structures.
• Experience with dbt Core/Cloud and SQL transformations.
• Know-how of orchestrating with Airflow and SQL optimization.
• Hands-on AWS: Athena, Lambda, Aurora, Glue, SageMaker.

Responsibilities

• Develop, maintain, and improve scalable data ingestion and processing pipelines.
• Code development: modify Lambda functions, SQL queries, and processing jobs.
• Data modeling using Iceberg for silver and gold layers.
• Query optimization for performance and cost efficiency.
• Apply data quality rules and automated checks.
• Ensure pipelines run reliably with external data sources.
• Document data preparation, transformations, code, and decisions clearly.
• Version control with GitLab using meaningful commits and practices.

Skills

Python development

TDD

AI-assisted coding

CI/CD

IaC

Data modeling

dbt core

Airflow

SQL

Iceberg

Athena

Spark

AWS services

Lambda

Aurora

EventBridge

Glue

SageMaker

Tools

GitLab

Job description

Seargin is seeking a data engineering professional to build and maintain scalable data pipelines. You will design data models with Iceberg, optimize SQL and Spark workloads, and apply automated data quality checks. The role emphasizes Python development, TDD, and AWS services integration in an international setting.

Join a team delivering complex data solutions and leverage modern tools like dbt and Airflow to ensure robust, scalable data platforms across environments.