Remote Data Engineer - Real-Time ELT & AI Capabilities

Andersen; Warszawa; Hybrid; PLN 181,000 - 336,000; Full time

Benefits offered by this job

Private health insurance

Sports compensation

Referral program

AWS/PMP certification funding

Mentoring and onboarding program

Hybrid/remote work options

Job summary

Andersen is looking for a Data Engineer to modernize a cloud-based quality intelligence platform and build scalable data solutions for analytics, security, and AI capabilities. The role involves handling batch pipelines, data ingestion from multiple sources, and shaping data for ML/analytics in Redshift.

You will own end-to-end data workflows, mentor junior engineers, and contribute to a hybrid work model with strong emphasis on reliability and scalability.

Qualifications

• 4+ years of end-to-end ELT/ETL data pipeline experience in cloud data warehouses.
• Expert-level SQL skills and production Redshift experience.
• Experience with incremental loads, CDC, SCD2, and near-real-time processing.
• Experience migrating legacy ETL to cloud platforms with minimal disruption.
• Experience with MySQL sources (incl. MariaDB).
• Proficient in AWS S3 and IAM for data landing and access control.
• Familiar with Airflow and dbt.

Responsibilities

• Monitor batch pipelines and debug failures in production.
• Trace failures across bronze/silver/gold layers and validate in a test env.
• Set up failure alerting for batch runs.
• Progress toward near-real-time data refresh with incremental loads.
• Ingest new data sources: connect, land in S3, define Redshift schema, grant IAM access.
• Expose data to ML engineers via views/materialized views.
• Review PRs and mentor junior engineers, ensuring performance budgets.
• Onboard quickly to align with platform architecture and philosophy.

Skills

SQL

Airflow

dbt

Redshift

English proficiency

Tools

AWS S3

IAM

Snowflake

SQL Server

Job description

Andersen is looking for a Data Engineer to modernize a cloud-based quality intelligence platform and build scalable data solutions for analytics, security, and AI capabilities. The role involves handling batch pipelines, data ingestion from multiple sources, and shaping data for ML/analytics in Redshift.

You will own end-to-end data workflows, mentor junior engineers, and contribute to a hybrid work model with strong emphasis on reliability and scalability.