Senior Data Engineer

Sigma Software Group

. Write and defend diagnostic SQL queries against large-scale production datasets .

Posted 11/9/2026full-timeRemote • PolandSeniorWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in Data Engineering with a strong focus on building and maintaining large-scale analytics pipelines, SQL query optimization, and data quality validation. Proficient in cloud data warehousing, particularly with BigQuery, and experienced in implementing data privacy practices.

Highest-signal resume keywords

Expert-Level SQL SkillsStrong Python SkillsExperience with Spark or PySparkExperience Designing ETL / ELT PipelinesExperience with GCP Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQL Query WritingData Pipeline DevelopmentData ModelingFeature Table DevelopmentData Quality ValidationEvent-Driven DatasetsStreaming Ingestion SystemsStatistical ValidationIncremental Processing PatternsDelayed Label Handling

Soft Skills

Analytical SkillsProblem-Solving SkillsOwnership-Oriented MindsetStrong Communication SkillsCollaborative Attitude

Tools & Technologies

BigQueryAirflowCloud ComposerTerraformKubernetesDataflowPub/SubGCSBeamDbt

Industry Keywords

AdTechAuction-Based EnvironmentsGDPRCCPAHybrid CloudLinux EnvironmentsProduction MLAnalytics PipelinesExperimentation InfrastructureClickstream Datasets

Tech Stack

Tools & technologies

AirflowBigQueryCloudETLGoogle Cloud PlatformKubernetesLinuxPySparkPythonSparkSQLTerraform

About the role

Key responsibilities & impact

Write and defend diagnostic SQL queries against large-scale production datasets
Build and maintain ingestion pipelines for bid, win, and impression logs into BigQuery
Harmonize fields across independently designed datasets and maintain versioned field mappings
Develop point-in-time-correct feature tables and aggregation pipelines
Design and maintain conversion and labeling pipelines with delayed label handling
Own the data serving write path, schema contracts, publishing flows, and freshness SLOs
Build experimentation infrastructure including traffic splitting and reporting pipelines
Perform large-scale historical backfills and safe reprocessing after mapping changes
Implement data isolation and safe-aggregation controls for advertiser data protection
Develop automated data quality validation frameworks
Collaborate closely with Customer engineers and prepare operational documentation
Contribute to architecture discussions and platform scalability improvements

Requirements

What you’ll need

5+ years of experience in Data Engineering
At least 2 years of experience working with production ML or large-scale analytics pipelines
Expert-level SQL skills including window functions and incremental processing patterns
Strong Python skills for production-grade pipeline development
Hands-on experience with Spark or PySpark
Experience designing ETL / ELT pipelines with Airflow, Cloud Composer, Dagster, or similar tools
Experience working with cloud data warehouses at scale, preferably BigQuery
Strong understanding of data modeling and point-in-time correctness
Experience working with event-driven or clickstream datasets at very large scale
Experience supporting business-critical production pipelines
Upper-Intermediate English level or higher
Experience with GCP services including Dataflow, Pub/Sub, GCS, and Beam
Experience building streaming or near-real-time ingestion systems
Understanding of feature stores, train/serve skew, and label leakage prevention
Experience in AdTech or auction-based environments
Experience handling delayed or incomplete labels in ML systems
Experience with dbt or similar transformation frameworks
Experience delivering solutions into Customer-owned infrastructure
Knowledge of GDPR/CCPA-related privacy engineering practices
Experience with experimentation infrastructure and statistical validation pipelines
Experience working in hybrid cloud/on-prem Linux environments
Terraform and Kubernetes experience
Experience optimizing warehouse cost and performance
Strong analytical and problem-solving skills
Ownership-oriented mindset
Ability to work independently in a client-facing environment
Strong communication and documentation skills
Comfortable working in a fast-paced engineering environment
Collaborative and proactive attitude

Benefits

Comp & perks

Opportunity to work on impactful global products
Collaborate with experienced engineers
Contribute to architecture decisions
Grow expertise in large-scale distributed systems and modern data platforms