09/09/2026 updated
100 % available
Senior Databricks Data Architect / Data Engineer
Oulu, Finland
Only remote
Bachelor of Science in Computer ScienceData AnalysisGoogle BigQueryData As A ServicesData ArchitectureData AuditingWeb ScrapingExtract Transform Load (ETL)Python (Programming Language)Microsoft SQL Server Data Engine (MSDE)SeleniumSQL DatabasesPySpark
Databricks & Big Data
Expertise in Databricks, Apache Spark, PySpark, Delta Lake, Databricks SQL, and Unity Catalog for designing and operating scalable lakehouse platforms and medallion architectures.
Data Engineering
Strong command of Python, SQL, ETL/ELT processes, data pipeline development, data modeling, and data quality management across enterprise-scale workloads.
Cloud Platforms
Broad experience with AWS, Azure, GCP, S3, and ADLS for building and deploying cloud data architectures and scalable data infrastructure.
Data & Analytics
Proficiency with Snowflake, PostgreSQL, SQL Server, Power BI, Tableau, and data warehousing concepts to support analytics, reporting, and business intelligence.
Orchestration & DevOps
Hands-on experience with Databricks Workflows, Apache Airflow, Azure Data Factory, CI/CD pipelines, Git, and Docker for automated deployment and workflow orchestration.
Infrastructure as Code & Automation
Practical use of Terraform and dbt for infrastructure automation, data transformation, and scalable deployment of data platforms.
Performance Optimization
Optimization of Spark workloads through partitioning, incremental processing, cluster configuration, and query tuning to improve reliability and cost efficiency.
Expertise in Databricks, Apache Spark, PySpark, Delta Lake, Databricks SQL, and Unity Catalog for designing and operating scalable lakehouse platforms and medallion architectures.
Data Engineering
Strong command of Python, SQL, ETL/ELT processes, data pipeline development, data modeling, and data quality management across enterprise-scale workloads.
Cloud Platforms
Broad experience with AWS, Azure, GCP, S3, and ADLS for building and deploying cloud data architectures and scalable data infrastructure.
Data & Analytics
Proficiency with Snowflake, PostgreSQL, SQL Server, Power BI, Tableau, and data warehousing concepts to support analytics, reporting, and business intelligence.
Orchestration & DevOps
Hands-on experience with Databricks Workflows, Apache Airflow, Azure Data Factory, CI/CD pipelines, Git, and Docker for automated deployment and workflow orchestration.
Infrastructure as Code & Automation
Practical use of Terraform and dbt for infrastructure automation, data transformation, and scalable deployment of data platforms.
Performance Optimization
Optimization of Spark workloads through partitioning, incremental processing, cluster configuration, and query tuning to improve reliability and cost efficiency.
Experience
Professional experience5 - 10 years
Freelancer since2024
Languages
EnglishFluent
Project history
Architected Databricks lakehouse platforms supporting enterprise analytics, machine learning, and data engineering. Designed Delta Lake pipelines, medallion architectures, Unity Catalog governance, and scalable Spark workloads. Improved reliability and cost efficiency through workload optimization, cluster configuration, incremental processing, and automated deployment. Tech Stack: Databricks, PySpark, Python, SQL, Delta Lake, Unity Catalog, AWS, Azure, Terraform, dbt.
Designed modern data platforms using Databricks, Spark, cloud storage, and analytics warehouses. Built ELT pipelines, data models, orchestration workflows, and data-quality controls for enterprise workloads. Improved scalability through distributed processing, optimized Spark jobs, and infrastructure automation. Tech Stack: Python, PySpark, Databricks, SQL, dbt, Azure, Terraform, Airflow, Snowflake.
Built scalable Python and SQL data pipelines for analytics, reporting, and cloud data platforms. Developed ETL workflows and dimensional models for high-volume enterprise datasets. Improved pipeline performance through Spark optimization, partitioning, incremental processing, and query tuning. Tech Stack: Python, SQL, Apache Spark, Databricks, AWS, PostgreSQL, ETL, Git.