... Transformation services leveraging SAP, Salesforce, Databricks, Snowflake, Application Modernisation and various AI projects. We are looking to add experienced Data Scientist to expand our Microsoft Practice with the below responsibilities: Experience & Education #Bachelor's or Master's degree in Computer Science, AI, Electronics, ...
Skills Required ~ Data Science Duties & Responsibilities Advanced statistics, predictive analytics. Advanced object-oriented programming Hadoop, MySQL, TensorFlow, Spark Machine learning, data modeling Good aptitude and communication Education & Training ~ IT Education
... Working knowledge of implementing CI / CD pipelines. Log analysis and monitoring using Splunk Databricks, AWS, Snowflake. What were looking for: - Bachelors / Masters degree in computer science / engineering from a reputed university - 10+ years of experience in data warehousing, data management, and team management. - More ...
About this Position The Data Engineer supports the development and operation of Henkel's enterprise metadata platform, DataHub. The role focuses on building scalable data engineering and governance solutions that connect key enterprise platforms into one centralized ecosystem serving global data consumers. As part of a ...
... & querying of the data 2) Providing business specific data solutions for various business streams like Payments, Finance, Consumer & Delivery Experience. The Data Engineer will play a key role in performing data extraction, data transformation, building and managing data pipelines to ensure data availability for ML & LLM ...
As a Senior Data Loss Prevention (DLP) , you will work as a part of our Cyber Security team, and you will collaborate with other IT professionals to ensure that sensitive data is protected from unauthorized access misuse, and breaches. Educational qualifications & Experience: - Bachelor’s/Master's degree in computer science, ...
... transformations and data structures for data warehouse and lake/repository. - Manage cloud and/or on-premises solutions for data transfer and storage. - Process data using spark (PySpark) - Manage cloud and/or on-premises solutions for data transfer and storage. - Collaborate and work with data analysts in various functions ...
... Consent Vendor Risk Execute end to end DSR DSAR workflows and privacy operations Perform data discovery classification and scanning using BigID Build and maintain data inventory catalog and lineage Identify sensitive data and risks PII overexposure dark data Support RoPA DPIA and regulatory compliance initiatives Configure workflows ...
... driven to deliver high quality data solutions that enable better decision making across the organization. This Data Engineer role will design, build, and maintain data pipelines and integrations across multiple source systems in a global environment. They develop ETL processes and APIs, manage data warehouse schemas, and ensure ...
... across technical and non-technical stakeholders. Preferred Qualifications - Experience with containerization technologies (Docker, Kubernetes). - Knowledge of data pipelines, data warehousing, or big data tools. - Familiarity with monitoring tools and performance optimization techniques. What’s in it for you? Pathways for ...
... and ML technology Shield key processes and know-how on Statistical and ML Guarantee highest ML utilization Education: Mathematics/Physics/Engineering with a master's in business/data analytics or proven track record on Data Science Proven track record of minimum 5 years as a data scientist Coding capabilities in R and/or ...
... degree or equivalent in Computer Science, MIS, Mathematics, Statistics, or similar discipline. Master's degree or PhD preferred. Relevant work experience in data engineering based on the following number of years: Fluency in English Planning & Organizing Skills Data Modeling and Database Design ETL (Extract, Transform, ...
... demonstrate hybrid Data Scientist capabilities alongside the ability to design, develop and deliver applications that provide business insights. GCIO & GCOO Data is a global team within CTO Data that delivers data governance, data management, MI / reporting and analytics for key Businesses and Group Organizational infrastructure ...
... intelligence. We empower the world's leading brands and retailers with unmatched insights into consumer behavior and the influencers that drive it. The entry of required data, as specified in the applicable detailed entry and category guidelines provided. General data entry guidelines that define how different fields are to be recorded ...
... Deliver data access projects for customers on time and effectively Work with the data team to improve processes and methodology Create new tooling to streamline data processing when called upon or when the opportunity presents itself Ability to work independently in a fast-paced Agile environment Bachelor's or Master's Degree ...
We are looking for a Big Data Architect with experience designing scalable data solutions using Agile/SAFe practices, data mesh architecture, real-time streaming, cloud platforms, and modern data engineering technologies. The candidate should have a strong DataOps mindset and the ability to design solutions for testability, ...
We are looking for a skilled Data Engineer with strong experience in Python and AWS cloud technologies. The ideal candidate should have hands-on knowledge of building automation frameworks, managing test scripts, and working with various AWS services. This role requires good technical understanding, strong problem-solving ...
... https://jobeax.com/link/Dt0HlcGS2dYWmJNd Responsibilities :- Design and implement end-to-end data ingestion and transformation pipelines using Azure Data Factory to ensure seamless data flow across the enterprise.- Develop high-performance data processing solutions using PySpark and Databricks to handle large-scale datasets and complex analytical ...
... clear, quantifiable outcomes. Our company is the culmination of several successful firms, each a leader in its own right in cloud, artificial intelligence, and data. This convergence of talent and expertise is how we help businesses reach their own "inflection point," where chaotic data becomes a strategic asset, complexity ...