2,060 good data lab jobs in India.

... mapping, and change detection. - Ensure annotation accuracy, consistency, and adherence to defined quality standards (QA/QC frameworks) across all delivered datasets. - Define and continuously improve annotation guidelines, taxonomies, and labeling protocols in collaboration with Data Science and ML teams. - Stay current ...

Experience : 7+ years of experience in Data Engineering, Data Quality, or Data Governance. 3+ years of experience working on AWS Data Platforms. Strong hands-on expertise in: - Python - SQL - Data Quality Engineering - Data Profiling - Data Validation Frameworks - Experience building AI-powered data quality and governance ...

... roadmaps.- Establish and embed repeatable methodologies, engineering standards and AI delivery playbooks that can scale across multiple client engagements.- Collaborate with product managers, delivery managers and data science teams to translate business requirements into well-architected technical solutions.- Own and drive ...

Consultant Data Engineer Databricks | Azure | PySpark | Spark SQL - Bengaluru / Hyderabad / GurugramLooking for an experienced Data Engineer with strong expertise in Azure Databricks, PySpark, Spark SQL, Azure Data Factory (ADF), ADLS, ETL, and SQL. You will design scalable data pipelines, build modern Lakehouse solutions, ...

... performance and fast rendering across various access methods. ~ Data Sourcing & Preparation: Write and optimize complex SQL queries to extract and structure data specifically for consumption in Tableau. Utilize Tableau Desktop (or similar tools) for building reports with visualization. ~ Collaborate with stakeholders in ...

... and tools Knowledge of CI/CD pipelines and DevOps practices for data platforms Ideally experience with Apache Kafka/Confluent Platform, inc support CDC (Change Data Capture) solutions, and managing Kafka topics, schemas, connectors, and stream processing pipelines Good understanding of event-driven architecture and real-time ...

... implement, and deploy Machine Learning and Generative AI solutions across business functions.- Analyze large datasets, derive actionable insights, and build scalable analytical workflows.- Design and implement AI-powered applications using LLMs, RAG frameworks, AI Agents, and Prompt Engineering techniques.- Collaborate with ...

... and maintain scalable batch and real-time data pipelines for fraud analytics. Develop and optimize Spark-based data processing frameworks. Implement efficient data ingestion frameworks and integrate multiple data sources. Build and support Snowflake data warehouse and data lake solutions. Develop data models for reporting, ...

... Cloud Data Migration Leadership : Lead cloud migration projects, developing scalable Spark pipelines. Implement Bronze, Silver, and gold tables for scalable data systems. Optimize Spark code to ensure efficient cloud migration. Data Modeling : Develop and maintain data models with strong governance practices. Data Cataloging ...

... MIS/reporting transformation or migration, including report migration, rationalization, data mapping, reconciliation, UAT, and production validation. Knowledge of data governance, data quality, KPI standardization, and reporting controls. Experience automating manual reporting and implementing scalable, self-service reporting ...

... extraction, and analysis.- Assist in the design and implementation of data models within our data warehouse.- Collaborate with the broader project team to understand data requirements and deliver effective solutions.- Troubleshoot and resolve issues in data pipelines and data quality to ensure accuracy and availability.- Contribute ...

Role Overview The Lead Data Scientist is a senior technical role combining deep expertise in statistics, mathematics and data preparation with strong capability in machine learning and hands-on programming. The role leads complex analyses, develops scalable solutions and ensures work is rigorous, reproducible and aligned ...

... DevOps. Develop reusable, modular, and maintainable code following software engineering best practices and coding standard. Optimize application performance, scalability, and reliability for high-volume data processing workloads. Implement automated testing, including unit test cases using pytest. Collaborate with front end ...

... focus on Java, Microservices and Kafka Java Microservices Back end Developer Java Sprint boot Microservices with expected knowledge of Kafka, Basic knowledge of Database. Experience with TDD and BDD. Must have experience with one of cloud (GCP, AWS or Azure). Also experience with Kubernetes and containers - Hands-on experience ...

... Responsibilities: Design, develop, and maintain scalable ETL/ELT pipelines. Build and optimize data warehouses, data lakes, and data models. Develop highly available data ingestion and processing systems for large datasets. Collaborate with cross-functional teams to deliver data solutions. Ensure data quality, performance, ...

... responsible for designing robust data models and optimizing our Snowflake-based data warehousing environment to support complex business intelligence needs. You will collaborate closely with cross-functional product teams, data scientists, and senior stakeholders to translate intricate business requirements into scalable, high-performance ...

... management; Perform role of Data Team Lead (DTL). Comply with Good Clinical Practices (GCPs), applicable regulatory guidelines, SOPs, policies, and, where available, CDM guidance documents Client Management:. serve as primary point of contact for customer on data management deliverables. With minimal guidance, provide project ...

... and convenience in a seamless digital experience. Collaboration with Data Engineering Team Partner closely with our Data Engineering team to ensure efficient data collection, storage, and processing Collaborate in designing and optimizing data pipelines for seamless data movement Work jointly on data architecture decisions ...

... preparing data for prescriptive and predictive modeling. Data engineers also develop data set processes for data modeling, mining, and production, integrate new data management technologies and software engineering tools into existing structures, and collaborate with data scientists and analysts to ensure data accuracy and ...

... stations operating in environments with variable network connectivity. Data Architecture & Edge Ecosystem Design Design, build, and maintain a highly resilient, scalable data architecture capable of syncing, storing, and processing massive datasets from both centralized cloud services and distributed edge devices (battery swap ...