Data Engineer — Scalable Pipelines & Analytics

Digital Forms; Warszawa; On-site; PLN 180,000 - 240,000; Full time

Job summary

Digital Forms is seeking a Data Engineer to build and maintain scalable ETL/ELT pipelines that ingest data into a centralized Data Lake. The role requires designing robust data architectures for reporting and analytics and ensuring data quality across multiple systems.

You will collaborate with analysts and stakeholders, define data requirements, and monitor pipelines to ensure reliability. Knowledge of cloud platforms and data modeling is essential for success.

Qualifications

• Experience designing and maintaining data pipelines (ETL/ELT).
• Strong SQL and Python programming skills.
• Experience with data lakes and data warehouses (Snowflake, AWS S3, BigQuery).
• Familiarity with cloud platforms (AWS, GCP, Azure) and related data processing services.

Responsibilities

• Build and maintain scalable data pipelines (ETL/ELT) to collect, transform, and integrate data from various systems into a centralized Data Lake.
• Design and optimize data architectures for reporting and analytics purposes.
• Ensure data quality, security, and availability across systems.
• Collaborate with analysts and stakeholders to define data requirements and support business intelligence efforts.
• Monitor and troubleshoot data pipelines to ensure smooth operation.
• Stay updated on industry trends and best practices in data engineering.

Skills

ETL/ELT pipelines

SQL

Python

Data modeling

Airflow

Tools

Apache Airflow

Talend

Snowflake

AWS S3

BigQuery

GCP

Azure

Job description

Digital Forms is seeking a Data Engineer to build and maintain scalable ETL/ELT pipelines that ingest data into a centralized Data Lake. The role requires designing robust data architectures for reporting and analytics and ensuring data quality across multiple systems.

You will collaborate with analysts and stakeholders, define data requirements, and monitor pipelines to ensure reliability. Knowledge of cloud platforms and data modeling is essential for success.