... efficiency, cost modeling, capacity planning, and quality enhancements. Develop a deep understanding of systems and processes to extract insights from existing data while identifying and recommending IT enhancements to improve data quality. Develop strong partnerships with IT application owners and data management teams to ...
... Asia and Latin America. Within BNP Paribas Cardif, the 'Data & AI' department significantly contributes to the strategic ambition of making BNP Paribas Cardif a data and analytics-driven company. The development of Data and Analytics is identified as one of the pillars of Cardif's strategy. To achieve its goals in Data Management, ...
... CRM, and products - Turn ambiguous data problems into fully-specced, buildable projects - Prioritize ruthlessly across a large backlog: which verticals, which data sources, which quality fixes come first, and why - Own the data quality feedback loop — define how we catch bad data before customers see it, and drive the process ...
... Purpose/ Summary We are looking for a skilled Data Engineer with 1-2 years of experience in designing, building, and maintaining scalable data pipelines and data platforms. The ideal candidate should have strong expertise in SQL, Databricks, and Azure Data Factory (ADF. and hands-on experience working with large datasets ...
... Preparation Product Area, focused on building the next generation of finance data and processing services The team builds on a lakehouse architecture using Azure Databricks, Azure Data Factory and Azure Data Lake (Delta Lake) with Python being the main programming language and PySpark is used for large scale data engineering. ...
... observability for data systems. - Knowledge of data governance, metadata/catalogue tools, lineage and data quality frameworks (i.e. Strong grasp of security, data privacy and regulatory requirements (e.g., GDPR, data residency). - Professional certification such as Databricks or AWS (Solutions Architect / Specialty). Consulting ...
... architectures like RNNs and LSTM , BERT Should have worked with cognitive services from major cloud platforms like AWS and have a working knowledge of SQL and no-SQL databases. Ability to create data and ML pipelines for more efficient and repeatable data science projects using MLOps principles Keep abreast with new tools, algorithms ...
... factual accuracy, or comparing responses — when projects are available. While each project involves unique tasks, contributors may: - Carefully review provided data (text, images, or videos); - Label or classify content based on project guidelines; - Identify and flag factually incorrect, sensitive, inappropriate, or unclear ...
... - Solid understanding of data pipeline fundamentals, including ingestion, transformation, and loading (ETL/ELT) processes. - Must have experience with batch data processing (scheduling, dependencies, failure recovery, performance tuning). - Knowledge of data warehousing concepts and familiarity with relational databases. ...
... shape. Senior Data Scientist We have an opportunity for a Senior Data Scientist to join our Data Science team in Bangalore, reporting to the Senior Director, Data Science. In this pivotal role, you will drive advanced analytics and machine learning solutions that power our security, networking, and cloud data products. ...
Requirements Strong programming skills in Python and SQL. Experience with data processing leveraging programming skills in Python and Spark. In-depth understanding of the Kafka platform for (real-time) data ingestion and processing of high-volume data. Design and architect data flows and data management in a Cloud environment ...
... Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive ...
... governance principles, data quality checks on each data layer. - A successful history of manipulating, processing and extracting value from large disconnected datasets. - Working knowledge of message queuing, stream processing, and highly scalable big data data stores. - Strong project management and organizational skills. ...
... and mitigate data risks throughout the data lifecycle, including protection, retention, storage, use, and quality l Partner with technology teams to capture data sources, formats, and data flows so that data can be validated for downstream analytics and reporting l Investigate and document potential data quality issues, ...
... vector-based data pipelines for AI and GenAI use cases Develop scalable batch and streaming data pipelines using cloud-based data platforms (e.g., Snowflake or Databricks) Create and evolve semantic data models that transform raw data into analytics-ready, trustworthy datasets Build data preprocessing, validation, and quality-assurance ...
... Perform data cleaning and preprocessing to prepare datasets for analysis. Write complex SQL queries to extract, manipulate, and analyze data from relational databases. Work with cloud platforms (e.g., AWS, Azure, Google Cloud) to store, manage, and analyze data. Use statistical techniques and software to analyze datasets, ...
... reliable, well-documented data products that drive operational and strategic decision-making. The ideal candidate is comfortable operating independently across the data stack, takes ownership of their work, and communicates proactively with team members across time zones. Core Responsibilities ETL / Data Pipeline Development ...
... including generative AI and LLM-based approaches — using enterprise business data, knowledge graphs, business process intelligence, and structured and unstructured data assets. - Learn SAP's deep data and process context — data models, metadata structures, and business process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, ...
... with LangChain , RAG , and agent workflows Translate business goals into production-ready AI applications Work with prompt engineering , embeddings, and vector databases Collaborate with engineering, product, and data teams on performance optimization Deploy AI solutions on AWS, Azure, or GCP and ensure cloud efficiency Requirements: ...