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Senior Data Engineer (Databricks) @ Addepto
Design and optimize scalable data pipelines using Databricks, Apache Airflow, and Spark to process streaming and batch data for enterprise clients across industries like aerospace, energy, and automotive.
Data Engineer - Automation & Innovation Department
Build and maintain scalable data pipelines, automate ingestion from Kafka, MQ, SFTP, and databases, and optimize cloud-based processing in GCP using BigQuery, Dataflow, and Airflow.
Machine Learning Ops and Data Engineer
Builds and maintains ETL pipelines, deploys ML models to production, and monitors data and model performance using Python, SQL, Azure, and Docker.
Data Engineer - Large Language Models
Builds and maintains scalable data pipelines for large language models in healthcare, transforming medical datasets and enabling model training/evaluation on Snowflake and AWS.
Senior AI Data Engineer
Designs and operates enterprise-grade data and AI platforms using GitOps, building scalable ETL pipelines, feature stores, and RAG systems to power Netwrix’s security-focused AI products.
Technology Lead - Databricks Data Engineering
Lead a team to build and optimize Databricks-based ETL/ELT pipelines using Python/SQL, Delta Lake, and cloud platforms (Azure/AWS/GCP) for large-scale data processing.
Technology Lead - Databricks Data Engineering
Lead a Databricks-based data engineering team to build and optimize ETL/ELT pipelines, Delta Lake tables, and cloud data warehouses using Python, SQL, and Azure/AWS/GCP.
Senior Data Platform / Data Engineer
Build and scale Straumann’s AI data infrastructure, focusing on a Data Lakehouse, dataset versioning (DVC), and reliable pipelines that power dental AI products.
Technology Lead - Databricks Data Engineering
Lead a Databricks-based data engineering team to build and optimize ETL/ELT pipelines, Delta Lake tables, and cloud data warehouses using Python, SQL, and Azure/AWS/GCP.
Machine Learning Engineer/Data Engineer
Build and deploy ML models and data pipelines for a financial-services client’s new AI practice using Python, Spark, Hadoop, and SQL.
Lead Data Engineer (Spark) @ Addepto
Lead a team building scalable data pipelines and platforms for enterprises using Spark, Airflow, and cloud tech to process terabytes of streaming and batch data for analytics and ML.
Senior Data Engineer/ML
Senior Data Engineer/ML Engineer builds and deploys ML models and pipelines in a banking context using Python, Spark, and AWS services like SageMaker and Glue.
Data Engineer (Spark) @ Addepto
Build and maintain scalable data pipelines for large enterprises using Spark, Cloudera, and Airflow to process streaming and batch automotive, aerospace, and telecom data.
Data Engineer (Databricks) @ Addepto
Build and optimize scalable data pipelines using Databricks, Spark, and Azure to power AI/ML solutions for global enterprises across aerospace, energy, and automotive sectors.
Data Engineer - Databricks, BI
Builds and optimizes Databricks/Spark pipelines and Delta Lake models to power BI dashboards and ML workloads for a global brewer’s data ecosystem.
Senior Data Engineer (Product)
Build and own the data backbone for a headless ecommerce SaaS platform, transforming raw transactional data into scalable pipelines and APIs that power real-time dashboards for 300+ fashion brands.
Data Engineer (K/M)
Builds and maintains dentsu’s Google Cloud-based data platform, writing Python pipelines in Airflow, integrating marketing and semi-structured data, and modeling in BigQuery for analytics and reporting.
( K / M) AI Full-Stack Engineer (AI Agents) - Praca zdalna K/M
Build and maintain AI-powered full-stack applications and agentic systems for a pharmaceutical client using Python, AI frameworks (LangChain, LangGraph), and AWS.
AI Full-Stack Engineer — Hybrid (Kraków) | 6-Month Contract
Designs and builds AI-powered full-stack applications, including REST APIs, microservices, and LLM workflows, while optimizing performance and security in a hybrid Kraków office.
Senior Data Platform Engineer (DevOps)
Build and maintain cloud-based data platforms and pipelines using AWS/Azure/GCP, orchestration tools, and data processing services to enable scalable analytics and ML operations.