1,989 data scientist jobs in India.

... standards.- Develop and review Python-based data engineering solutions, frameworks, and reusable components.- Design and optimize ETL/ELT pipelines for large-scale data processing.- Work with structured and unstructured data across data lakes, data warehouses, and modern data platforms.- Define strategies for data ingestion, ...

... Advanced Python Programming, Databricks , Azure SQL , Data factory (ADF), Data Lake, Data storage, SSIS. Create and deploy scalable ETL/ELT pipelines with Azure Databricks by utilizing PySpark and SQL . Experience in Unity Catalog for centralized data governance, access control, and data lineage tracking. Develop unit tests ...

... cleansing, reusable query logic, automation of data pipelines.- SQL & Query Optimization : Advanced joins, indexing, stored procedures, query tuning for large datasets.- Microsoft Fabric : Exposure to Fabric ecosystem for scalable data engineering and analytics.- Data Modeling & ETL : Star schema, fact/dimension modeling, ...

... experience in Data Engineering. Data Engineer We are looking for a DevOps Engineer to join our team. The ideal candidate brings 4+ years of hands-on experience in Data Engineering. 4+ years of hands-on experience in Data Engineering. Strong SQL and database concepts. Proficiency in Python. Experience with ETL/ELT tools and data ...

... (Exposure preferred). Design and implement data pipelines using ETL/ELT tools and techniques. Configure and manage data storage solutions, including relational databases, data warehouses, and data lakes. Develop and implement data quality checks and monitoring processes. Automate data platform deployments and operations using ...

... candidates via LinkedIn, all applications must be submitted through our official website ( https://jobeax.com/link/1iJyEIRqk07JrVCp build systems that run on data, and that data has to be ingested, transformed, and validated before anything downstream can trust it. As a Data Engineer, you build the ingestion and transformation ...

... expertise in designing and managing Snowflake data warehouses, including performance tuning and resource monitoring.- Proficiency in building modular and scalable data transformations using Data Build Tool (dbt).- Advanced capability in writing complex SQL and Python scripts to manipulate large datasets and automate data processing ...

Responsibilities of the Intern: - Perform basic exploratory data analysis (EDA) to identify patterns and insights - Create simple visualizations, charts, and dashboards to present findings - Support the team in preparing data-driven reports and presentations - Work with team members to understand project goals and contribute ...

... around the world. Job Summary: Electrical Engineer with experience on FEED, proposal & detailed engineering preferably in an EPC industry for Manufacturing units, Data centers and Buildings/utility projects. Candidate should have exposure to Indian, US, Euro and other foreign codes/standards and local practices. Major Responsibilities: ...

... Collaborate with data scientists, analysts, and other engineers to understand data requirements and deliver solutions. Troubleshoot and resolve issues related to data pipelines and applications. Contribute to documentation of data pipelines and system architecture. Stay up-to-date with the latest Big Data technologies and trends. ...

... 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 ...

Key Responsibilities : Data Engineering & BI Modernization : - Design and build ETL/ELT pipelines to migrate legacy BI systems (SSRS, Cognos, legacy SSAS/OLAP cubes) to modern cloud data platforms (Snowflake, Databricks, Azure Synapse, BigQuery, or similar).- Re-architect and optimize data models (star/snowflake schemas, ...

Key Responsibilities : Data Engineering & BI Modernization : - Design and build ETL/ELT pipelines to migrate legacy BI systems (SSRS, Cognos, legacy SSAS/OLAP cubes) to modern cloud data platforms (Snowflake, Databricks, Azure Synapse, BigQuery, or similar).- Re-architect and optimize data models (star/snowflake schemas, ...

... unstructured data. Build and manage modern cloud-based data platforms, data lakes, and data warehouses. Ensure data quality, integrity, governance, and security across data ecosystems. Collaborate with cross-functional teams to understand business requirements and translate them into technical data solutions. Optimize data workflows ...

... Dimensions (SCD), Entity and Grain Definition, KPI and Metric Design, Semantic Layer Development, Data Transformation and Aggregation, Structured and Semi-Structured Data, JSON / Nested Data, NoSQL concepts, Snowflake and/or Databricks, Practical Python, Data Quality, Reconciliation, and Validation, Analytical Data Warehousing ...

... scalable ETL pipelines for large-scale data processing.- Build and optimize distributed data applications using Spark and Scala.- Develop reliable, high-performance data pipelines for batch and streaming workloads.- Work with large datasets to ensure data quality, consistency, and performance.- Collaborate with engineering, product, ...

... BigQuery and advanced SQL.- Experience with Dataform or dbt.- Hands-on experience with Cloud Composer/Apache Airflow.- Experience with Dataflow/Apache Beam and/or Dataproc/Spark.- Strong understanding of data modelling, schema evolution, data quality, and data pipelines.- Experience with batch and streaming data processing.- ...

... call support days: 12:30pm-9:30pm Requirements - Minimum 3 yrs exp. in Data and production support hands on skill, handling incidents - Python - Must have - Databricks - Must have - Unity Catalog - Must have - ADLS - Must have - Spark - Must have - Job Orchestration (Airflow) - Must have - Data pipeline Architecture and ...

... MLOps/LLMOps practices covering model and application deployment, versioning, monitoring, evaluation, observability, and lifecycle management.- Collaborate with Data Scientists, ML Engineers, Software Engineers, Product teams, and business stakeholders to translate requirements into scalable AI solutions.- Troubleshoot, optimize, ...

... MLOps/LLMOps practices covering model and application deployment, versioning, monitoring, evaluation, observability, and lifecycle management.- Collaborate with Data Scientists, ML Engineers, Software Engineers, Product teams, and business stakeholders to translate requirements into scalable AI solutions.- Troubleshoot, optimize, ...