... 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. ...
... 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 ...
... 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 ...
... 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. ...
... - 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. ...
... PyTorch, Scikit-learn. - Familiarity with cloud platforms (AWS, Azure, GCP, SAP Cloud Platform) and container tools (Docker, Kubernetes). - Understanding of data engineering, ETL pipelines, and big data technologies (Spark, Hadoop, Kafka). - Proficiency with software engineering best practices (CI/CD, Git, testing, modular ...
... 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, ...
... 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, ...
... 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 ...
... 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: ...
... potential can thrive. The Role Required Skills and Experience - •Expertise in data mining, data storage and Extract-Transform-Load (ETL) processes - •Experience in data pipelines development and tooling, e.g., Glue, Databricks, Synapse, or Dataproc - •Experience with both relational and NoSQL databases, PostgreSQL, DB2, MongoDB ...
... LangChain, LlamaIndex, and Hugging Face. Orchestration: LangGraph and Multi-Agent Systems (MAS). Development: Python, FastAPI, and Asynchronous Programming. RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies. ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management, ...
... degree in data science, Mathematics, Statistics, Computer Science, or related field AND 5+ years related experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR master's degree in data science, Mathematics, Statistics, Computer Science, or related field AND 4+ ...
... Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer ...
... in sales processes focused around value selling, prospecting and opportunity qualification - Ability to adapt to a fast paced environment - Passion for cloud, big data and AI About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, ...
... 2-3 years as Data/Backend Engineer with PM work (PRDs, roadmaps, user research) Technical Stack Depth Deep understanding: ETL/ELT pipelines, data warehousing, data lakes/lakehouses Advanced SQL (query optimization, not just SELECT statements) Hands-on with ONE of: Hive/Spark/Hadoop/HDFS, Snowflake/Databricks/BigQuery, or ...
... business needs and data volumes. Champion modern data architecture patterns including data products, data contracts, observability, self-service capabilities, metadata-driven architectures, and AI-assisted engineering practices. Data Products & Business Impact Lead the design and delivery of data products that generate measurable ...