195 Data Engineer jobs in India available for remote work from home. Apply for positions such as Data Engineer, Data Engineer, Data Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design, build, and maintain scalable data pipelines and infrastructure for batch and real-time data processing. Collaborate with cross-functional teams to ensure high-quality, reliable, and accessible data for analytics and machine learning applications.
Design, develop, and maintain scalable data pipelines and ingestion strategies using Snowflake, Python, and PySpark. Collaborate with cross-functional teams to implement data quality rules, governance, and security across all storage layers.
Build and maintain scalable ETL/ELT pipelines and real-time data streaming solutions using AWS and Kafka. Manage data warehouse optimization in Redshift and ensure data quality and observability through automated checks.
Design, build, and maintain scalable data pipelines and management systems to support AI/ML and LLM applications. Collaborate with engineers to optimize data models, ensure data quality, and manage cloud-based data infrastructure.
Design, build, and maintain reliable data pipelines and integrations between PostgreSQL databases, AWS services, and internal applications. Collaborate with AI and software teams to develop scalable platform architecture and data infrastructure for renewable energy initiatives.
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Design, develop, and optimize scalable data integration pipelines and ETL/ELT processes using the Azure ecosystem and Microsoft Fabric. Partner with stakeholders to translate business requirements into reliable data engineering solutions and support the migration of legacy on-premises systems to the cloud.
Design and maintain scalable AWS data platforms and pipelines for batch and streaming workloads. Implement data governance, normalization workflows, and knowledge graphs to support analytics and AI/ML use cases.
The Data Engineer will implement and optimize data integration pipelines and ensure data quality and governance within the Salesforce ecosystem. They will also develop workflows for data migration and contribute to analytics and reporting solutions.
The Data Engineer will design, build, and optimize ETL/ELT workflows and develop scalable data pipelines. They will also collaborate with cross-functional teams to deliver impactful data solutions.
Design, develop, and maintain scalable data engineering applications using GCP, Spark, Hive, and BigQuery. Collaborate with product teams to translate requirements into technical solutions and support production environment deployments.
You will architect and maintain resilient, high-scale data extraction pipelines using a mix of deterministic parsers and LLM-based systems. You will also own the end-to-end ETL infrastructure, ensuring data quality, observability, and performance across the platform.
The Senior Data Engineer will design, build, and operate scalable, cloud-native data solutions and batch/streaming pipelines for enterprise clients. They will collaborate with stakeholders to ensure data platforms are secure, tested, and optimized for performance.
You will architect and build scalable, fault-tolerant data pipelines and semantic layers to support analytics and AI initiatives. Additionally, you will own end-to-end data quality, observability, and the integration of Generative AI frameworks into enterprise data solutions.
You will build next-generation agentic systems by bridging raw data with actionable AI to create autonomous agents that reason and execute complex workflows. The role involves designing data models for AI consumption and maintaining high-performance production standards.
Design, build, and optimize large-scale data pipelines and lakehouse solutions using the Databricks platform. Collaborate with cross-functional stakeholders to solve complex data engineering problems while mentoring junior team members.
You will be responsible for building and maintaining core front-end features, including web and desktop clients, while focusing on data insights and reporting. This involves collaborating with other teams, participating in code reviews, and delivering high-quality, secure software solutions.
![Smart Working Solutions is hiring for remote Lead Data Engineer (Contract, Full-Time) [HR207]](/assets/08150176-369d-44db-a4a7-778571334971.png){kind=small}
You will architect and build scalable data infrastructure to support AI-driven operational platforms for property management. This role involves defining data engineering standards, managing real-time pipelines, and collaborating with cross-functional teams to translate data capabilities into product decisions.
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You will be responsible for all aspects of data collection and ingestion to support model training operations. This includes operating cloud infrastructure and collaborating with scientists to optimize data quality and cost.
The role involves managing data collection and ingestion pipelines to support AI model training at scale. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap.
The Senior Data Engineer will build and maintain ETL/ELT pipelines to ingest advertising data into Snowflake and optimize data models for analytics. They will also manage AWS-based infrastructure and collaborate with the engineering team to integrate new data sources and DSP connections.
The Principal Data Engineer will act as a technical lead and architect to build world-class data solutions that drive business decisions. They will also mentor a team of engineers and define the technical direction for data engineering capabilities.
The role involves managing data collection and operating cloud infrastructure to support large-scale model training operations. You will collaborate with scientists and leadership to optimize data pipelines and define the AI team's dataset roadmap.
The role involves managing data collection and ingestion pipelines to support large-scale model training operations. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap for AI products.
You will influence product teams and partner with data consumers to ensure the quality and usefulness of data assets. Additionally, you will be responsible for architecting, modeling, and transforming data while leading projects to drive business strategy.
Design, build, and maintain scalable data pipelines and infrastructure for batch and real-time data processing. Collaborate with cross-functional teams to ensure high-quality, reliable datasets for analytics and machine learning applications.
You will architect, design, and deliver scalable data engineering solutions while mentoring junior engineers and driving best practices. The role involves managing ETL/ELT pipelines, optimizing data warehouse performance, and enabling self-service analytics for business stakeholders.
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You will own the data infrastructure, pipeline reliability, and reporting layers to ensure high-quality, actionable insights for the organization. Additionally, you will act as an analytical partner for the Growth and Product teams to drive commercial decisions and marketing performance.
Design, develop, and test distributed software applications while ensuring fault tolerance and service availability. Coordinate with engineering teams to resolve urgent issues and leverage monitoring tools to solve complex problems at scale.
Design, develop, and maintain scalable data pipelines for ingestion, processing, and storage while ensuring data quality and security. Collaborate with cross-functional teams to deliver data solutions that meet business needs and monitor pipeline performance.
You will design, build, and operate scalable, cloud-native data pipelines and platforms using modern ETL/ELT approaches. The role involves collaborating with cross-functional teams to ensure production-ready solutions and mentoring junior engineers.
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