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 Spark and Delta Lake
• Build ingestion, transformation, and curation workflows for structured and unstructured data
• Implement lakehouse patterns and medallion layering across bronze, silver, and gold layers
• Contribute to cloud-to-cloud migrations, including re-platforming pipelines and data models
• Deliver production-grade datasets for analytics, machine learning, causal modeling, and optimization
• Build data pipelines for GenAI use cases, including LLMs, RAG, vector-based data flows, and agent-based architectures
• Leverage Databricks MLflow and Unity Catalog or equivalent tooling
• Design logical and physical data models
• Orchestrate workflows with Databricks Workflows, Airflow, dbt, or equivalents
• Apply event-driven and streaming architecture patterns
• Ensure data governance, lineage, quality, and access control using Unity Catalog, AWS Lake Formation, Microsoft Purview, or GCP Dataplex
• Establish observability for data freshness, pipeline reliability, and SLA adherence
• Enable serving layers such as APIs, feature inputs, and analytical endpoints
• Optimize pipelines and infrastructure for performance, scalability, and cost
• Understand stakeholder needs, challenge requirements, and surface better alternatives
• Collaborate with data scientists, ML engineers, analysts, platform teams, and business stakeholders
• Support adoption of data products and contribute to best practices

• Experienced Senior Data Engineer
• Strong hands-on experience with Apache Spark and Delta Lake
• Strong Python and SQL
• Proven experience building batch and streaming pipelines and production-grade data platforms
• Solid understanding of data modeling, data quality, and governance
• Strong, demonstrable hands-on experience with the Databricks Lakehouse Platform
• Deep expertise in at least one major cloud: AWS, GCP, or Azure/Fabric
• Openness and ability to work across clouds
• Experience with lakehouse architectures and distributed systems
• Strong understanding of scalability, reliability, and performance
• Naturally curious, with strong problem-solving skills and a collaborative approach in cross-functional teams
• Comfortable challenging business requirements
• Adaptable and eager to work across platforms
• Agile or consulting experience is beneficial
• Nice-to-have: experience across more than one cloud or cloud migration experience
• Nice-to-have: Snowflake experience
• Nice-to-have: GenAI and AI data systems, including RAG pipelines, vector databases, and LLM data preparation
• Nice-to-have: CI/CD for data pipelines and infrastructure-as-code, including Terraform and CloudFormation
• Nice-to-have: streaming technologies such as Kafka, Spark optimization, or ML/experimentation platforms
• Nice-to-have: experience building data products or large-scale analytics platforms

• Flexibility, with hybrid work options and 25 vacation days for a healthy work-life balance
• Co-subsidized transportation & Multisport cards
• Premium health insurance for fast and easy access to top healthcare services
• Training policy for technical and other skills-related events, courses and certifications
• Personal career development roadmap guided by performance evaluations
• Self-care program offering psychological consultations & discussions for you and the team
• Cozy office space designed for comfort and productivity
• Exciting team events and company gatherings
• Growth opportunities
• Values-driven culture
• International careers
• Inclusive culture and accessibility support