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- Sr. Data Engineer:
Core Skills – Data Engineering, Big Data, Pyspark, Spark SQL and Python
Candidate with prior Palantir Cloud Foundry OR Clinical Trial Data Model background is preferred
Major accountabilities:
- Responsible for Data Engineering, Foundry Data Pipeline Creation, Foundry Analysis & Reporting, Slate Application development, re-usable code development & management and Integrating Internal or External System with Foundry for data ingestion with high quality.
- Have good understanding on Foundry Platform landscape and it’s capabilities
- Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
- Defines company data assets (data models), Pyspark, spark SQL, jobs to populate data models.
- Designs data integrations and data quality framework.
- Design & Implement integration with Internal, External Systems, F1 AWS platform using Foundry Data Connector or Magritte Agent
- Collaboration with data scientists, data analyst and technology teams to document and leverage their understanding of the Foundry integration with different data sources - Actively participate in agile work practices
- Coordinating with Quality Engineer to ensure the all quality controls, naming convention & best practices have been followed
Desired Candidate Profile :
- Strong data engineering background
- Experience with Clinical Data Model is preferred
- Experience in
- SQL Server ,Postgres, Cassandra, Hadoop, and Spark for distributed data storage and parallel computing
- Java and Groovy for our back-end applications and data integration tools
- Python for data processing and analysis
- Cloud infrastructure based on AWS EC2 and S3
- 7+ years IT experience, 2+ years’ experience in Palantir Foundry Platform, 4+ years’ experience in Big Data platform
- 5+ years of Python and Pyspark development experience
- Strong troubleshooting and problem solving skills
- BTech or master's degree in computer science or a related technical field
- Experience designing, building, and maintaining big data pipelines systems
- Hands-on experience on Palantir Foundry Platform and Foundry custom Apps development
- Able to design and implement data integration between Palantir Foundry and external Apps based on Foundry data connector framework
- Hands-on in programming languages primarily Python, R, Java, Unix shell scripts
- Hand-on experience in AWS / Azure cloud platform and stack
- Strong in API based architecture and concept, able to do quick PoC using API integration and development
- Knowledge of machine learning and AI
- Skill and comfort working in a rapidly changing environment with dynamic objectives and iteration with users.
Demonstrated ability to continuously learn, work independently, and make decisions with minimal supervision
A Desktop Support Engineer is responsible for providing technical support and assistance to end-users in an organization. This role involves troubleshooting hardware and software issues, ensuring that desktop systems are functioning efficiently, and maintaining a high level of customer satisfaction.
Key Responsibilities:
- Respond to user inquiries and provide technical support via phone, email, or in-person.
- Diagnose and resolve hardware and software problems, including operating systems, applications, and network connectivity issues.
- Install, configure, and upgrade desktop hardware and software, ensuring compliance with company standards.
- Maintain inventory of desktop equipment and software licenses, ensuring proper documentation and tracking.
- Collaborate with IT teams to implement new technologies and improve existing systems.
- Provide training and support to users on new software applications and tools.
- Assist in the setup and deployment of new workstations and peripherals.
- Monitor and maintain system performance, applying updates and patches as necessary.
- Document technical procedures and solutions for future reference.
Qualifications:
- Bachelor’s degree in computer science, information technology, or a related field, or equivalent experience.
- Proven experience in a desktop support role or similar technical support position.
- Strong knowledge of Windows and macOS operating systems, as well as common software applications.
- Familiarity with networking concepts and troubleshooting techniques.
- Excellent problem-solving skills and the ability to work under pressure.
- Strong communication skills, both verbal and written, with a customer-focused attitude.
- Relevant certifications (e.g., CompTIA A+, Microsoft Certified Desktop Support Technician) are a plus.
This role is essential for maintaining the productivity of employees by ensuring that their desktop environments are operational and efficient. A successful Desktop Support Engineer will be proactive, detail-oriented, and able to work independently as well as part of a team.
We are looking for a Senior Data Engineer with strong expertise in GCP, Databricks, and Airflow to design and implement a GCP Cloud Native Data Processing Framework. The ideal candidate will work on building scalable data pipelines and help migrate existing workloads to a modern framework.
- Shift: 2 PM 11 PM
- Work Mode: Hybrid (3 days a week) across Xebia locations
- Notice Period: Immediate joiners or those with a notice period of up to 30 days
Key Responsibilities:
- Design and implement a GCP Native Data Processing Framework leveraging Spark and GCP Cloud Services.
- Develop and maintain data pipelines using Databricks and Airflow for transforming Raw → Silver → Gold data layers.
- Ensure data integrity, consistency, and availability across all systems.
- Collaborate with data engineers, analysts, and stakeholders to optimize performance.
- Document standards and best practices for data engineering workflows.
Required Experience:
- 7-8 years of experience in data engineering, architecture, and pipeline development.
- Strong knowledge of GCP, Databricks, PySpark, and BigQuery.
- Experience with Orchestration tools like Airflow, Dagster, or GCP equivalents.
- Understanding of Data Lake table formats (Delta, Iceberg, etc.).
- Proficiency in Python for scripting and automation.
- Strong problem-solving skills and collaborative mindset.
⚠️ Please apply only if you have not applied recently or are not currently in the interview process for any open roles at Xebia.
Looking forward to your response!
Best regards,
Vijay S
Assistant Manager - TAG
Job Description:
1.Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges
a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem
b. Improve Model accuracy to deliver greater business impact
c.Estimate business impact due to deployment of model
2.Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge
3.Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines
4.Design , develop & deploy Deep learning models using Tensorflow / Pytorch
5.Experience in using Deep learning models with text, speech, image and video data
a.Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc
b.Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV
c.Knowledge of State of the art Deep learning algorithms
6.Optimize and tune Deep Learnings model for best possible accuracy
7.Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau
8.Work with application teams, in deploying models on cloud as a service or on-prem
a.Deployment of models in Test / Control framework for tracking
b.Build CI/CD pipelines for ML model deployment
9.Integrating AI&ML models with other applications using REST APIs and other connector technologies
10.Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.
· Technology/Subject Matter Expertise
- Sufficient expertise in machine learning, mathematical and statistical sciences
- Use of versioning & Collaborative tools like Git / Github
- Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
- Develop prototype level ideas into a solution that can scale to industrial grade strength
- Ability to quantify & estimate the impact of ML models.
· Softskills Profile
- Curiosity to think in fresh and unique ways with the intent of breaking new ground.
- Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control
- Ability to think ahead, and anticipate the needs for solving the problem will be important
· Ability to communicate key messages effectively, and articulate strong opinions in large forums
· Desirable Experience:
- Keen contributor to open source communities, and communities like Kaggle
- Ability to process Huge amount of Data using Pyspark/Hadoop
- Development & Application of Reinforcement Learning
- Knowledge of Optimization/Genetic Algorithms
- Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
- Optimize and tune deep learning model for best possible accuracy
- Understanding of stream data processing, RPA, edge computing, AR/VR etc
- Appreciation of digital ethics, data privacy will be important
- Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
- Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus
Responsibilities:
- Responsible for monitoring project deliverables on day to day basis
- Required to update relevant stakeholders or team members on the project's progress.
- Assist, train, and ensure project team members with tasks that you have assigned to them.
- Test the product modules and manage the change request, bug reports, etc.
- Assist project managers in the planning, execution, and monitoring of projects Develop and maintain project plans, timelines, and progress reports.
- Facilitate communication between intern stakeholders, clients, vendors, and management.
Qualifications:
- Bachelor's Degree or equivalent experience.
- 3+ years of relevant Project Management experience.
- Strong verbal, written, and organizational skills for documentation, user stories, etc.
- Proficient in MS Excel, and Presentation. Proficient in Jira, Confluence, and Notion is a plus.
- Excellent organizational and time-management skills.
- Strong communication skills, both verbal and written.
- Ability to work well in a team environment.
- Experience with project management tools and software.
- Ability to identify project risks and issues, and develop mitigation plans.
- Essentail Skills:
- Docker
- Jenkins
- Python dependency management using conda and pip
- Base Linux System Commands, Scripting
- Docker Container Build & Testing
- Common knowledge of minimizing container size and layers
- Inspecting containers for un-used / underutilized systems
- Multiple Linux OS support for virtual system
- Has experience as a user of jupyter / jupyter lab to test and fix usability issues in workbenches
- Templating out various configurations for different use cases (we use Python Jinja2 but are open to other languages / libraries)
- Jenkins PIpeline
- Github API Understanding to trigger builds, tags, releases
- Artifactory Experience
- Nice to have: Kubernetes, ArgoCD, other deployment automation tool sets (DevOps)
- Hands on experience in following is a must: Unix, Python and Shell Scripting.
- Hands on experience in creating infrastructure on cloud platform AWS is a must.
- Must have experience in industry standard CI/CD tools like Git/BitBucket, Jenkins, Maven, Artifactory and Chef.
- Must be good at these DevOps tools:
Version Control Tools: Git, CVS
Build Tools: Maven and Gradle
CI Tools: Jenkins
- Hands-on experience with Analytics tools, ELK stack.
- Knowledge of Java will be an advantage.
- Experience designing and implementing an effective and efficient CI/CD flow that gets code from dev to prod with high quality and minimal manual effort.
- Ability to help debug and optimise code and automate routine tasks.
- Should be extremely good in communication
- Experience in dealing with difficult situations and making decisions with a sense of urgency.
- Experience in Agile and Jira will be an add on




