Thermo Fisher Scientific
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Bengaluru · On-site · 10-13 Yrs · 4 days ago
Biotech & Pharmaceuticals · 10000+ Employees · Waltham, US
As the world leader in serving science, we empower our people to advance innovative technologies, develop meaningful solutions, and build rewarding careers. With annual revenue of approximately $40 billion and the largest investment in R&D in the industry, we give our 100,000 extraordinary minds the resources and opportunities to make significant contributions to the world. Explore the professional possibilities at Thermo Fisher Scientific, and join us.
Hiring: Engineering
What employees say
+ Great technology stack and learning opportunities. Good exposure to modern automation tools and frameworks.
− I have experienced a significant amount of workplace politics during my 8 months here. At times, I have felt a lack of inclusiveness and found it challenging to feel like a local t
More reviews on the company profile.
Interview experience · Software Automation Tester
Before interview just go through the online questions. Interviewer read out the questions from another screen ask the same. But it's a good one to know some of the topics which which not required in your daily automation
Average difficulty · Bengaluru · 157 reports
More interview insightsJob description
Overview
Environmental Conditions
Responsibilities
- We are seeking an experienced Sr. Data Platform Engineer to build and operate secure, scalable data platforms and deliver reliable data, AI, generative AI, and analytics solutions using Databricks, Apache Spark, and modern cloud technologies.
- The role combines platform engineering, data engineering, AI/ML enablement, business intelligence, and operational support, working closely with engineering, data science, analytics, security, DevOps, architecture, and business stakeholders.
- Configure and manage Databricks workspaces, clusters, policies, runtimes, and separate Development, QA/UAT, and Production environments.
- Implement platform security and governance using Unity Catalog, IAM/RBAC, service principals, secrets, private connectivity, and enterprise access controls.
- Automate Databricks infrastructure and deployments using Terraform, source control, and CI/CD practices.
- Build and maintain scalable ETL/ELT pipelines and Lakehouse solutions using Apache Spark, PySpark, Databricks workflows/jobs, and Delta Lake.
- Integrate Databricks with enterprise data sources, cloud storage, databases, APIs, and downstream applications.
- Optimize Spark workloads, queries, clusters, and resource usage for performance, reliability, scalability, and cost.
- Prepare data and build ML workflows covering feature engineering, model training, evaluation, deployment, and lifecycle management using Databricks and MLflow.
- Develop generative AI solutions using LLMs, prompt engineering, embeddings, vector search, retrieval-augmented generation, and model serving.
- Evaluate and monitor AI solutions for accuracy, relevance, safety, bias, latency, cost, privacy, and governance.
- Create analytical datasets, semantic models, KPIs, dashboards, and reporting layers using Databricks SQL and tools such as Power BI, Tableau, or Looker.
- Translate business requirements into accurate, performant, user-friendly dashboards and self-service analytics solutions.
- Ensure analytics solutions follow applicable data governance, security, quality, and accessibility standards.
- Establish monitoring, logging, alerting, troubleshooting, and operational support for data, AI, generative AI, and analytics workloads.
- Collaborate across architecture, security, infrastructure, engineering, data science, analytics, and business teams to define practical Databricks standards and best practices.
- Maintain concise technical documentation for platform configuration, deployment, data pipelines, AI workflows, dashboards, and operational procedures.
Qualifications
- Role: Senior Data Platform Engineer
- Primary Skills: Databricks, Apache Spark/PySpark, Python, SQL, Delta Lake, Unity Catalog, MLflow, GenAI, BI, Cloud, CI/CD, Terraform
- At least 10 years of professional experience building analytics platforms, including at least 5 years of hands-on Databricks experience; a Databricks certification is required.
- Strong production experience with Databricks, Apache Spark/PySpark, Python, SQL, Delta Lake, Lakehouse architecture, workspaces, clusters, jobs/workflows, and scalable ETL/ELT pipelines.
- Working experience with MLflow and AI/ML/GenAI delivery, including model lifecycle, LLMs, embeddings, vector search, RAG, prompt engineering, and model serving.
- Strong troubleshooting, performance optimization, monitoring, and production-support skills.
- Knowledge of data governance, metadata management, data-quality frameworks, BI governance, privacy controls, and responsible AI practices.
- Additional Databricks certifications or relevant cloud certifications, and experience in regulated or large enterprise environments, are a plus.
- Strong analytical, troubleshooting, and outcome-oriented problem-solving skills.
- Strong ownership of reliable, secure, scalable, and maintainable solutions.
- Ability to collaborate effectively across engineering, data science, analytics, architecture, DevOps, security, and business teams.
- Ability to translate business needs into practical data, analytics, and AI solutions.
- Clear verbal and written communication, including concise technical documentation.
- Strong attention to data governance, security, privacy, responsible AI, and operational discipline.
Education
- Bachelor’s or
- master’s degree in computer science, Information Technology, Engineering, or a related discipline.
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Job application FAQ
Last updated 3 October 2026
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- This listing is marked on_site with location Bengaluru, Karnataka. Confirm details on the job description before applying.
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- This is a senior Sr. Data Platform Engineer role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.