Senior Data Engineer

• Design, build, and optimize modern cloud-based data platforms powering analytics, AI, and data products
• Develop reliable batch, streaming, and near-real-time pipelines using technologies such as Spark and Delta Lake
• Build ingestion, transformation, and curation workflows for structured and unstructured data
• Implement lakehouse architectures and medallion layering within Databricks or Fabric
• Deliver curated datasets for analytics, machine learning, causal modeling, and optimization systems
• Enable GenAI pipelines, including LLM, RAG, vector-based, and agent-based data flows
• Design scalable logical and physical data models
• Orchestrate workflows using Airflow, dbt, Databricks Workflows, Azure Data Factory, or equivalents
• Apply data governance, lineage, quality, access control, and security best practices
• Establish observability for data freshness, pipeline reliability, and SLA adherence
• Enable data-serving layers such as APIs, feature inputs, and analytical endpoints
• Monitor and optimize pipelines and infrastructure for performance, scalability, and cost efficiency
• Discover, derive, and refine business requirements with stakeholders
• Collaborate with data scientists, ML engineers, analysts, platform teams, and business stakeholders
• Support adoption of data products and contribute to data and AI ecosystem best practices

• Experienced Senior Data Engineer
• Strong hands-on experience with Apache Spark and Delta Lake
• Strong programming skills in Python and SQL
• Proven experience building batch and streaming data pipelines
• Experience building production-grade data platforms
• Solid understanding of data modeling, data quality, and governance principles
• Strong, demonstrable hands-on experience with AWS data services and the Databricks Lakehouse Platform, or Microsoft Azure/Fabric services and tooling
• Deep expertise in at least one of the AWS or Azure/Fabric platform tracks
• Experience with lakehouse architectures and distributed data systems
• Strong understanding of scalability, reliability, and performance considerations in data pipelines
• Strong problem-solving skills and collaborative approach to cross-functional work
• Familiarity with Snowflake or GCP is a plus but not required
• Experience in Agile or consulting environments is beneficial
• Experience with both AWS and Azure/Fabric, GenAI and AI data systems, CI/CD for data pipelines, Terraform or CloudFormation, Kafka, Spark optimization, advanced analytics, ML workloads, data products, or large-scale analytics platforms is nice to have
• No educational credential is specified

• Private health insurance
• Education program with training and certification
• Wellbeing program
• Free coffee, drinks, and snacks at work
• Company dinners
• Company events, including ski trips, karting, laser-tag, wine tasting, picnics, and cooking classes
• Competitive salary
• 24 days of vacation
• Annual company events with the whole team
• Challenging projects
• Inclusive culture and support for growth
• Open feedback culture
• Reasonable accommodations during the interview process