Senior Data Engineer

SOFTETA

. Propose and lead the architecture for user-data workflows across Airflow, Spark, dbt, and BigQuery, including encryption points, derived tables, backfills, and partitions.

Posted 10/31/2026full-timeKraków • PolandSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in designing and leading user-data workflows using Airflow, Spark, dbt, and BigQuery, with a strong focus on engineering best practices, data lifecycle validation, and regulatory compliance. Proven ability to mentor teams and establish standards for code quality and incident resolution.

Highest-signal resume keywords

AirflowSparkDbtBigQueryPython

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Pipeline MigrationData Lifecycle ValidationCode ReviewsTesting ProtocolsIncident ResolutionEncryption At RestData Retention PoliciesEvent-Driven ArchitecturesRefactoring Production PipelinesMentoring

Soft Skills

Technical Leadership

Tools & Technologies

GCP KMSBigQuery AEAD FunctionsTinkGoogle Cloud Data CatalogApache Kafka

Industry Keywords

GDPREngineering Best Practices

Tech Stack

Tools & technologies

AirflowApacheBigQueryCloudGoogle Cloud PlatformKafkaPythonSpark

About the role

Key responsibilities & impact

Propose and lead the architecture for user-data workflows across Airflow, Spark, dbt, and BigQuery, including encryption points, derived tables, backfills, and partitions.
Sequentially migrate existing pipelines behind a custom regression harness to guarantee identical output.
Establish engineering standards post-migration, including 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).

Requirements

What you’ll need

Deep hands-on experience with Airflow, Spark, dbt, BigQuery, and Python.
Proven track record leading a live pipeline migration technically from conception to completion.
Hands-on experience refactoring production pipelines while verifying identical output.
Demonstrated success establishing engineering best practices (testing, code reviews, incident resolution) within a team.
Concrete mentoring or technical leadership experience.
Previous experience with encryption at rest, data retention policies, or regulatory compliance (e.g., GDPR).
Envelope encryption using key management services (GCP KMS), BigQuery AEAD functions, or Tink.
BigQuery column-level security, policy tags, and Google Cloud Data Catalog.
Event-driven architectures using Apache Kafka.

Benefits

Comp & perks

Diverse and technically challenging projects.
Training budget for professional and personal growth.
Flexible working hours and a hybrid workplace model.
Flexible schedule and an Agile/SCRUM environment.
Technical equipment that you can choose.