Senior Data Engineer: Pipelines & Migration (Hybrid)

Softeta; Kraków; Hybrid; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Hybrid workplace model

Flexible working hours

Training budget for growth

Choice of technical equipment

Job summary

Softeta is seeking an experienced Senior Data Engineer to join a telecommunications project, leading the architecture, migration, and optimization of production data pipelines using Airflow, Spark, dbt, BigQuery, and Python.

You will drive end-to-end migration behind a regression harness, establish engineering standards, implement verification jobs, and mentor the team while collaborating with stakeholders across data platforms.

Qualifications

• Extensive hands-on data engineering with Airflow, Spark, dbt, BigQuery, and Python.
• Proven ability to lead complete pipeline migrations from design to production.
• Ability to establish engineering standards: testing, reviews, incident handling, release checklists.
• Experience documenting decisions with Architecture Decision Records (ADRs).
• Mentor or provide technical leadership within a team.

Responsibilities

• Propose and lead architecture for user-data workflows across Airflow, Spark, dbt, and BigQuery (encryption points, derived tables, backfills, partitions).
• Migrate existing pipelines behind a custom regression harness to guarantee identical output.
• Establish lasting engineering standards post-migration: code reviews, testing protocols, incident post-mortems, and release checklists.
• Implement verification jobs to validate end-to-end data lifecycle rules.
• Participate in pipeline maintenance, incident response, and root-cause resolution.
• Document design choices using Architecture Decision Records (ADRs).

Skills

Data architecture

Data migration

Technical leadership

Code reviews

Testing protocols

Incident resolution

ADR documentation

Mentoring

Tools

Airflow

Spark

dbt

BigQuery

Python

Job description

Softeta is seeking an experienced Senior Data Engineer to join a telecommunications project, leading the architecture, migration, and optimization of production data pipelines using Airflow, Spark, dbt, BigQuery, and Python.

You will drive end-to-end migration behind a regression harness, establish engineering standards, implement verification jobs, and mentor the team while collaborating with stakeholders across data platforms.