... patient behaviour modellingHealthcare recommendation systemsMedical NLP and clinical language understandingData quality and clinical entity modellingFeatures and datasets for foundation and generative AI modelsYou will work closely with ML engineers, clinicians, product managers and data engineers to take ideas from research ...
... experience in Data engineering. Pyspark with GCP and AWS,Snowflake and Data bricks are required skills. Working with data excites you; You can build and operate data pipelines, and maintain data storage, all within distributed systems. You have hands-on experience of data modeling and modern data engineering tools and platforms. ...
... https://jobeax.com/link/tlplQAnK5B36KMXq Responsibilities :- Design, develop, and maintain scalable data pipelines using Azure data services.- Build and optimize ETL/ELT processes using Azure Data Factory (ADF).- Develop data integration solutions using Azure Databricks, PySpark, and Spark SQL.- Design and implement data lakes using Azure Data Lake Storage ...
Data Modeller / Data Engineer Location – PAN India As a Senior Data Modeller / Data Engineer, you will be responsible for designing and implementing enterprise‑grade data models and scalable data engineering solutions across cloud and on‑premise ecosystems. The role requires deep expertise in conceptual, logical, and physical ...
... improved efficiency, and stronger operational performance. Role: Senior Data Scientist Location: Bangalore- Karnataka (Hybrid) Experience: 5+ years Department: Data Science Role Overview We are looking for individuals who sit at the intersection of Data Science and Physical Sciences . You understand that industrial data isn't ...
... SAP MDG, or similar data management solutions. - Strong knowledge of SQL, Windows Server, APIs, cloud platforms (Azure and AWS), infrastructure, GitHub, and DataDog. - Understanding of data governance, metadata management, data quality, and master data management concepts. - Experience with automation and scripting tools ...
... Development Team. The ideal candidate should have strong skills in data handling, statistical analysis, and visualization tools, along with the ability to translate data into meaningful insights. Key Responsibilities : Data Analysis : - Collect, clean, and validate large datasets from multiple sources - Analyze data to identify ...
... for our next Data Intelligence Manager to have the following skills and experiences: - 3-5 years of experience in a data analytics, business intelligence, or data intelligence role - Strong proficiency in SQL and hands-on experience building dashboards in Power BI - Experience working with large datasets across multiple ...
... infrastructure supporting enterprise data platforms.- Establishes enterprise-wide data quality controls, validations, and monitoring frameworks.- Serves as the senior data engineering subject matter expert and technical authority for the organization.- Leads large and complex data engineering projects and major components of enterprise ...
... proper documentation and approvals. Collaborate with business teams on data governance and compliance initiatives. Identify and implement best practices for data ingestion, data design, and data quality improvement. Develop queries for profiling data, validating analyses, testing assumptions, and driving data quality assessment. ...
... Overview :We are looking for a proactive Data Support Engineer to join our data engineering team. The role involves supporting, monitoring, and troubleshooting data pipelines and ETL processes, ensuring data reliability and smooth operations across Snowflake-based data https://jobeax.com/link/tlplQAnK5B36KMXq Responsibilities ...
Welcome to Gallagher in India — where expertise, technology, and purpose come together. Since 2006, Gallagher in India has supported global teams by delivering quality, service, and speed through deep expertise, smart technology, and specialized knowledge services.
... pipelines to ingest, transform, and validate data from marketplace, inventory, and sales sources Build and maintain SQL data lake storage so historical and change data stays available for analysis Automate recurring data jobs (e.g., via Rundeck) and monitor them for failures and data anomalies Use AI tools to accelerate pipeline ...
Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Apache Spark, ...
... business needs into technical solutions by designing data models and reports Perform exploratory data analysis and implement automated data quality checks Optimize data feeds and ensure timely data availability using Change Data Capture and other approaches Maintain data governance by enforcing best practices in data quality, ...
Required Skills :- Solid hands-on experience in various databases, data mining and data analysis methods, utilizing advanced data tools, writing complex SQL queries.- Data preparation, data analysis, identify insights from raw data.- Analyses metrics, key indicators and other available data sources to discover root causes ...
... Spark/PySpark.- Build and manage data workflows using Azure Data Factory, Azure Databricks, and Synapse Analytics.- Design and implement ETL/ELT processes for data ingestion and transformation.- Integrate data from multiple sources and ensure reliable data movement across platforms.- Optimize data processing jobs, queries, ...
Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Data Engineering ...
... for batch and real-time data processing. Build and optimize ETL/ELT workflows to collect, transform, and load data from multiple sources. Develop and maintain data models, data warehouses, and data lakes. Ensure data quality, consistency, accuracy, and reliability across data pipelines. Optimize data processing workflows ...