Senior Data Engineer

🔥 9 minutes ago

🇵🇱 Poland – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• Design and build scalable cloud-native data platforms from greenfield to production • Design and implement near-real-time ingestion pipelines using event-driven patterns • Define and enforce data platform standards including Data Lake/Lakehouse principles, medallion architecture, and data contracts • Refactor, optimize, and modernize Spark and PySpark scripts for performance and maintainability • Introduce best practices for code quality, testing, and CI/CD across data pipelines • Drive adoption of AI tooling and agentic workflows within the data engineering team • Ensure data quality, observability, and reliability across pipelines and platforms • Design and deliver self-service tooling and microservices that abstract platform complexity • Collaborate directly with the Customer’s scientific and engineering teams • Monitor platform performance, reliability, and cloud infrastructure costs

🎯 Requirements

• 5+ years of experience in data engineering • 3+ years of production experience with Databricks and Delta Lake • Strong expertise in medallion architecture and event-driven asynchronous pipeline design • Advanced proficiency in Python, PySpark, and SQL • Deep hands-on experience with Databricks, including Unity Catalog, Lakeflow Jobs/Workflows, and job optimization • Strong AWS expertise including S3, IAM, KMS, AWS Batch, ECR, EventBridge, Lambda, or API Gateway • Experience with infrastructure as code and CI/CD using Terraform and Databricks Asset Bundles • Practical experience with Git workflows, pull request reviews, and automated testing • Experience configuring secure CI pipelines using OIDC or service principals • Practical MLflow experience including experiment tracking, model registration, and reproducibility practices • Strong understanding of data quality, lineage, provenance, schema contracts, and versioning • Experience with data quality frameworks such as Great Expectations, Soda, pyDeequ, or Databricks Labs DQX • Experience with monitoring, observability, and cloud cost optimization • Upper-Intermediate English level or higher • Strong analytical mindset • Ownership and accountability • Ability to communicate complex technical concepts clearly • Proactive approach to problem-solving • Attention to scalability and maintainability • Collaborative and team-oriented attitude • Plus: Experience packaging workloads in Docker containers and running batch jobs on AWS • Plus: Familiarity with scikit-optimize, BoTorch, Ax, and scipy • Plus: Experience building feature sets and train/test splits that avoid data leakage • Plus: Experience with regulated or high-security environments including data residency requirements • Plus: Experience disabling or restricting AI features in secured environments

🏖️ Benefits

• Employees can work remotely • Opportunity to work on innovative global projects • Opportunity to contribute to breakthrough research in clean energy and fusion science • Driving engineering excellence, automation, and AI adoption within the data platform ecosystem