... software architecture and infrastructure for managing data applications. They are involved in developing core capabilities which include technical and functional data platforms. They are the anchor for functional streams of work and are accountable for timely delivery. They work on the latest big data tools, frameworks and ...
... (Pandas, Polars) and modern big data tools such as Databricks (Spark), Flink, or Kafka. - Strong understanding of data pipeline development, ETL frameworks, and data lakes/warehouses. - Extensive experience with cloud data platforms such as AWS (S3, Redshift, Lambda, Glue), GCP (BigQuery, Dataflow, Dataproc), or Snowflake. ...
About ORANTS AI: ORANTS AI is a cutting-edge technology company at the forefront of AI and Big Data innovation. We specialize in developing advanced marketing and management platforms, leveraging data mining, data integration, and artificial intelligence to deliver efficient and impactful solutions for our corporate clients. ...
... scalable. Authoring and design of Big Data ETL platforms and pipelines in SCOPE, Scala, SQL, Python, or C# Data extraction across a wide variety of data sources Data cleaning, preprocessing, and transformation for further analysis by data analysts Data Validation framework from source to endpoints ensuring data quality and ...
... optimization and performance tuning experience Data Engineering: Experience with data orchestration platforms (Airflow, Azure Data Factory, SSIS, or similar) Big Data: Familiarity with Apache Spark, PySpark, or similar distributed processing frameworks Cloud Platforms: Hands-on experience with Azure, AWS, or GCP data services ...
... retail banks, investment banks, broker-dealers & asset management firms, and insurance firms from leading Fortune 500 Companies. Within EY’s Consulting Practice, Data and Analytics team solves big, complex issues and capitalize on opportunities to deliver better working outcomes that help expand and safeguard the businesses, ...
... optimization and inference efficiency. - Experience with cloud platforms (AWS, Azure, or GCP) and MLOps for scalable AI deployments. - Proficiency in working with big data technologies (Spark, Hadoop, SQL, NoSQL databases). - Strong problem-solving skills with the ability to translate business challenges into AI-driven solutions. ...
... Data Analysis and Engineering - Develop and optimise data models to support analytical requirements. - Conduct ETL processes to extract, transform, and load data efficiently into Google BigQuery. - Utilise Pandas for data manipulation, ensuring cleanliness and reliability of datasets. - Create efficient queries to retrieve ...
... challenge of setting the course for large company wide initiatives, building and launching customer facing products in international locales, this may be the next big career move for you. We are building systems which can scale across multiple marketplaces in automated large scale ecommerce business. We are looking for a QAE ...
... security. Debug and troubleshoot issues to ensure smooth application functionality. Participate in code reviews and contribute to team knowledge sharing. Work with databases such as MsSQL, MySQL, or PostgreSQL. Implement security and data protection best practices. Qualifications - 6–8 years of experience in backend development ...
... a Senior Data Engineer to operate & design, manage & maintain, and optimize our data platform. In this role, you will bridge the gap between traditional big data engineering and modern Generative AI infrastructure. You will be responsible for building robust data pipelines on Databricks, engineering high-quality datasets ...
... Qualifications: - 7+ years of experience in data engineering and analytics, with a strong background in designing scalable database architectures, building and optimizing data pipelines, and applying statistical analysis to deliver strategic insights across complex, high-volume data environments - Deep knowledge of big data frameworks ...
... and manages vendors engaged in big data analysis. - Designs data mining frameworks and statistical protocols to extract and monitor patterns within high-volume datasets across functional business domains. - Applies cutting-edge data science principles and machine learning techniques to create models that support strategic ...
... clients build world class products. We offer an array of services including Core Business Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud Adoption, Mobility, Digital Adoption, Agile & DevOps, Quality Assurance ...
... plus. - SQL Experience. - GenAI experience in one or all of Prompt Engineering, RAG, Fine-tuning is a must to have, Agentic AI is a plus to have. - Knowledge of Data Warehouses (Snowflake, BigQuery, Redshift, Synapse). - Experience with version control systems, such as Git/Github. - Big Data processing framework experience ...
... experience in the analytics domain Working knowledge of Python/R Proficient in advanced SQL / Excel / Google Sheets and analysis. Experience in handling large datasets and deriving insights out of it Data visualization and data storytelling skills Knowledge of Big Data processing tools like Qubole/Databricks/Spark Ability ...
... when https://jobeax.com/link/0a2QmNkVhUZFALjk Candidate will have :- Experience with Agentic AI, Generative AI, LLMs, and prompt engineering.- Experience with big data technology stack (Hadoop, Spark, HDFS, EMR, Glue).- Experience with AWS, Azure or GCP.- Experience with Databricks/SageMaker/DataRobot, MLFlow or other ML ...
... Preferred Skills: Experience with Big Data technologies , including Spark, Kafka, and Scala, for Distributed Data processing. Hands-on expertise in working with AWS Big Data services such as EMR, DynamoDB, Athena, Glue, and MSK (Managed Streaming for Kafka). Familiarity with on-premises Big Data platforms and tools for Data Processing ...
... Vector Databases (Pinecone, FAISS, OpenSearch, etc.) LangChain, LangGraph, Agentic AI frameworks Prompt engineering, orchestration, and AI governance practices Big Data & Analytics Data processing frameworks: Data platforms: Data Lakes, Lakehouse architectures SQL & NoSQL databases Data governance, quality, and metadata ...
The EDO Sustainable1 DATA OPERATIONS team at S&P Global is a project-focused, international group dedicated to excellence in sustainability data management. We are responsible for one of the world's most complete datasets on corporate sustainability, supporting global investors, corporates, and stakeholders with in-depth ...