Sr. Data Platform Engineer
Core
Design, build, and operate secure, scalable data platforms and deliver reliable data, AI, and analytics solutions using Databricks and modern cloud technologies.
Role type
Senior Data Platform Engineer (Staff Engineer level)
Builds
Secure, governed Databricks workspaces; scalable ETL/ELT pipelines and Lakehouse solutions; production-ready AI/GenAI workflows; trusted analytics dashboards and reporting layers.
Domain
Data Engineering, AI/ML, Generative AI, Cloud Infrastructure
Required skills
Databricks, Apache Spark/PySpark, Python, SQL, Delta Lake, Unity Catalog, MLflow, GenAI, BI, Cloud, CI/CD, Terraform (via careerplan.io/jobs/R-01370119-1-sr-data-platform-engineer-at-thermofisher)
Preferred skills
Databricks Asset Bundles, Apache Airflow, Azure Data Factory, Spark Structured Streaming, Kafka, Event Hubs, LangChain, LlamaIndex, Hugging Face, Azure OpenAI, Amazon Bedrock, fine-tuning, model evaluation
Technologies
Databricks, Apache Spark, PySpark, Delta Lake, Unity Catalog, MLflow, Terraform, Power BI, Tableau, Looker, Azure, AWS, Google Cloud
Responsibilities
Configure and manage Databricks workspaces, clusters, policies, and environments; implement platform security and governance using Unity Catalog and IAM/RBAC; automate Databricks infrastructure and deployments using Terraform and CI/CD; build and maintain scalable ETL/ELT pipelines and Lakehouse solutions; optimize Spark workloads for performance and cost; prepare data and build ML workflows covering feature engineering, model training, and lifecycle management; develop generative AI solutions using LLMs, prompt engineering, embeddings, and vector search; create analytical datasets, semantic models, KPIs, and dashboards; establish monitoring, logging, alerting, and operational support for data and AI workloads.
Seniority
Senior, hands-on IC with architectural guidance
