Senior Data Engineer

Job not on LinkedIn

🔥 56 minutes ago

🇵🇱 Poland – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

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Sigma Software Group

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2002

💼 Consulting

🏥 Healthcare

🚘 Automotive

Consulting • Healthcare • Automotive

Sigma Software Group is a multinational company, established in 2002, that specializes in providing high-quality software development, graphic design, testing, and support services. The company focuses on delivering solutions across various industries such as automotive, telecommunications, aviation, advertising, gaming, banking, real estate, and healthcare. Sigma Software values professional growth, offers remote work opportunities worldwide, and caters to world-renowned clients like AstraZeneca, Scania, and SAS. The company emphasizes a culture of continuous education, mentorship, and flexible work environments, making it a preferred workplace for IT specialists aiming to work on complex solutions utilizing cutting-edge technologies. Sigma Software is committed to innovative solutions and engineering the future while also contributing to social causes such as charitable work in Ukraine.

📋 Description

• 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

• 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 • 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 • 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

🏖️ Benefits

• Opportunity to work on impactful global products • Collaboration with experienced engineers • Opportunity to contribute to architecture decisions • Opportunity to grow expertise in large-scale distributed systems and modern data platforms

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