2,026 real data entry jobs in India.

Roles & Responsibilities :- Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.- Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.- Integrate and orchestrate ...

... environment.- Experience with data quality frameworks, metadata management, lineage tooling, and transaction-level reconciliation.- Working knowledge of cloud data services, workflow orchestration, infrastructure as code, and CI/CD for data pipelines.- Understanding of data protection, access control, encryption, retention, ...

... NoSQL databases (PostgreSQL, MySQL, DynamoDB). Familiarity with DevOps practices and CI/CD tools (Jenkins, GitHub Actions). Experience with Kafka or Kinesis for real-time data streaming. Knowledge of Terraform, CloudFormation, or CDK for infrastructure automation. Hands-on experience with data security and governance . Strong ...

... seamless data integration, high data quality, and secure access while collaborating with stakeholders to translate business needs into efficient, cloud-optimized data solutions. Key Responsibilities: - Design, build, and maintain scalable data pipelines and ETL processes including database scripts, stored procedures, triggers, ...

... and sellers of high-demand consumer goods from around the world using dynamic pricing mechanics. This approach affords access and market visibility powered by real-time data that empowers buyers and sellers to determine and transact based on market value. The StockX platform features hundreds of brands across verticals including ...

... cross-functional teams to transform complex data into meaningful reports and recommendations. The Data Analyst will be responsible for collecting, cleaning, and analyzing data from multiple sources to identify trends and opportunities. Responsibilities Collect, clean, and analyze data from multiple sources to identify trends and opportunities. ...

... journey of model building Advocating application of best practices in data engineering, code hygiene, and code reviews Leading the development of proprietary data engineering, assets, ML algorithms, and analytical tools on varied projects Working with partners and principals to shape proposals that showcase our data engineering ...

... semantic models and governed data products they can trust Must-Have Experience - 5+ years hands-on data engineering on cloud data platforms — Snowflake and/or Databricks demonstrated in real project delivery, not skill-list-only - Direct hands-on experience with either Snowflake Cortex or Databricks Genie — you have built, ...

... requirements. Identify and correct data inconsistencies and anomalies. Use data labelling tools such as Labelbox, Supervisely, Scale AI, or similar platforms. Data Quality Assurance: Conduct quality checks on labelled data to ensure adherence to project standards. Work closely with data scientists, engineers, and product ...

... business, product, and engineering stakeholders in matrixed environments. Biopharma / healthcare domain exposure — commercial analytics, clinical development, real-world data, patient journeys, evidence generation, or regulated workflows. Fine-tuning / adaptation experience (PEFT, LoRA, QLoRA). Expertise in big data technologies ...

... maintain scalable data transformation pipelines using Python (with tools like PySpark, ADF...) and SQL in Azure Databricks.- Implement transformation logic to move data from Bronze to Silver/Gold layers following data engineering best practices.- Apply strong data engineering principles to ensure data reliability, quality, performance, ...

... and modern data platforms.- Experience designing end-to-end AI solutions and architectures across cloud and enterprise environments.- Strong understanding of data architecture concepts including data lakes, lakehouses, data warehouses, data pipelines, data governance, and data platforms.- Experience with major cloud platforms ...

... Responsibilities include: Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. Develop data pipelines to extract and transform data in near real-time using cloud-native technologies. Implement data validation and quality checks to ensure ...

Data Science Lead

... semantic and contextual foundation of SAP's AI. While generic AI agents operate on surface-level patterns, SAP agents are accurate because they understand the real semantics of enterprise business master data, process flows, and domain relationships. Your team will build and scale the layer that makes that possible. What ...

... and modern data platforms.- Experience designing end-to-end AI solutions and architectures across cloud and enterprise environments.- Strong understanding of data architecture concepts including data lakes, lakehouses, data warehouses, data pipelines, data governance, and data platforms.- Experience with major cloud platforms ...

... data analytics team. A significant portion of this role will focus on commercial analytics and business intelligence, including marketing and sales analytics, real-world data analysis (e.g., claims and EHR), and the design and delivery of dashboards and data visualizations that support strategic and operational decision-making. ...

... scientists, software engineers, and other stakeholders to support data acquisition, solution design, implementation, and ongoing maintenance. Design and implement data pipelines for batch, micro-batch, and real-time data streams. Ensure data quality by implementing data quality rules and test cases. Liaise with clients to gather ...

Job Responsibilities Data Governance professional with experience in: Data Governance & Stewardship Collibra SQL Customer Master Data (HCP, HCO, Affiliations, Organizations, Addresses, Territories & Sales Alignment) Data Quality, Validation, Deduplication & Enrichment Metadata Management, Data Lineage, Business Glossary ...

... parameterizations and translate them into equivalent Python EL scripts and dbt transformation models. • Develop and maintain Python EL pipelines to land high-volume data, including billion-row tables, into the target warehouse using SQLAlchemy, cx_Oracle, pyodbc, and bulk export tools such as Oracle Data Pump and SQL Server BCP. ...