Top Data Engineer Jobs in Bangalore

Design and assist data platform blueprint and components, collaborate with Integration and Data Architects, drive team decisions, provide cross-team solutions, and ensure cohesive integration, data quality and governance for cloud-based Snowflake implementations.

Design and help implement data platform components, collaborate with Integration and Data Architects, provide SME guidance, support data governance, and ensure integrated, secure cloud data solutions.

Designs and leads graph data solutions, including graph databases, data models, integration patterns, and scalable ETL pipelines. Collaborates with integration and data architects to develop cohesive platform blueprints. Builds and optimizes graph data ingestion and query performance using technologies such as Neo4j, TigerGraph, and AWS Neptune. Produces technical solution deliverables, supports data transformation and analytics initiatives, and communicates recommendations to clients and stakeholders.

Designs and supports Azure-based data platform architecture, integrating systems and data models with Integration and Data Architects. Builds analytics solutions, prototypes, data visualizations, and UX strategies using Power BI and related tools. Translates data and analytics strategies into technology solutions, documents designs, assesses quality, collaborates with stakeholders, follows release processes, and mentors junior engineers.

Designs scalable enterprise graph data solutions, including graph databases, data models, integration patterns, and data pipelines. Develops labeled property and ontology graph models for use cases such as fraud detection, recommendations, supply chain, and entity resolution. Collaborates with integration and data architects, performs graph integration and query optimization, supports analytics and operational use cases, and creates technical solution deliverables. Requires extensive IT experience, graph solution expertise, programming knowledge, and strong client-facing communication skills.

Designs scalable enterprise graph data solutions, including graph databases, models, integration patterns, and data pipelines. Collaborates with Integration and Data Architects to create cohesive data architectures. Develops graph models, ontologies, ETL processes, and graph query optimizations for analytical and operational use cases such as fraud detection, recommendations, supply chain, and entity resolution. Produces technical solution deliverables and supports client-facing requirements analysis, communication, and presentations.

Builds, maintains, and optimizes scalable batch and real-time data pipelines using Databricks, PySpark, Spark, Python, and cloud platforms. Develops ETL/ELT processes, data lakes, ingestion strategies, and Big Data frameworks. Collaborates with architects, data scientists, analysts, and engineers to ensure data accuracy and availability. Supports performance tuning, governance, security, orchestration, and deployment of cloud-native data solutions.

Designs and develops data platform blueprints, integrating systems, data models, and platform components. Collaborates with Integration and Data Architects, leads teams as a subject matter expert, makes technical decisions, resolves complex data issues, and recommends platform enhancements. Requires expertise in Large Language Models, data architecture, integration techniques, cloud-based data platforms, and troubleshooting.

Designs and supports data platform blueprints and components, collaborating with Integration and Data Architects to integrate systems and data models. Leads team decisions, provides solutions across teams, facilitates knowledge sharing, and optimizes database performance. Requires expertise in Graph Databases, data modeling, integration methodologies, cloud data platforms, and database troubleshooting, along with at least five years of experience and 15 years of full-time education.

Designs and supports data platform blueprints and components, collaborating with Integration and Data Architects to ensure cohesive system and data-model integration. Requires expertise in graph databases, data modeling, database design and optimization, integration methodologies, and troubleshooting. The role serves as a subject matter expert, manages team decisions and performance, supports multiple teams, and facilitates knowledge sharing.

Designs and governs cloud-native, AI-first data platform architectures for SAP customers. Leads architecture workshops, defines integration patterns, and designs domain-driven, event- and API-first systems. Establishes AI patterns including LLM, RAG, MCP, and vector search while enforcing security, IAM, reliability, observability, and DevSecOps practices. Coaches engineering teams and guides architecture decisions across application, data, and machine learning integration.

Designs scalable graph data solutions, including graph databases, data models, integration patterns, and data pipelines. Develops ontology and labeled-property graph models for use cases such as fraud detection, recommendations, supply chain, and entity resolution. Collaborates with integration and data architects, optimizes graph queries, supports analytical and operational data use cases, and delivers technical solutions while engaging clients and stakeholders.

Designs and maintains data models across conceptual, logical, and physical stages. Partners with clients, integration architects, and data architects to gather requirements, conduct discovery workshops, create solution blueprints, and secure deliverable sign-offs. Develops dimensional, 3NF, and NoSQL models; supports cloud database design, data warehousing, transformation, analytics, and data platform initiatives. Produces physical designs and DDL scripts for engineering implementation, estimates delivery work, and communicates solutions to clients.

Builds, maintains, and optimizes scalable batch and real-time data pipelines using Databricks, Spark, PySpark, and cloud platforms. Develops ETL/ELT and ingestion processes, supports data lakes and Big Data frameworks, tunes performance, and maintains governance and security practices. Collaborates with architects, data scientists, analysts, and engineers to ensure reliable data integration, accuracy, and availability.

Designs scalable enterprise graph data solutions, including graph databases, models, integrations, and data pipelines. Collaborates with Integration and Data Architects to develop cohesive data platform blueprints. Builds and optimizes graph-based ETL solutions, ontology and labeled-property models, and analytical data capabilities for use cases such as fraud detection, recommendations, supply chain, and entity resolution. Requires strong client-facing communication, technical solutioning, and data architecture skills.

Designs and leads graph data solutions, including graph databases, data models, integration patterns, and scalable ETL pipelines. Collaborates with integration and data architects to ensure cohesive system and data integration. Develops graph data ingestion and processing solutions using platforms such as Neo4j, TigerGraph, or AWS Neptune, optimizes query performance, and creates solution deliverables. Requires strong data architecture, transformation, analytics, client-facing, communication, and technical solutioning skills.

Designs and supports data platform blueprints, pipelines, integrations, and data models. Collaborates with architects and cross-functional teams to implement secure, governed, and performant data solutions. Monitors and troubleshoots platform performance, optimizes storage and retrieval, and contributes technical solutions independently while developing subject matter expertise.

Develops and supports scalable AWS data platforms and end-to-end ETL pipelines using AWS Glue, Lambda, PySpark, Python, and SQL. Collaborates with integration and data architects on platform blueprints, data models, and system integration. Designs cloud infrastructure, deploys code through GitLab CI/CD and CloudFormation, and works with Redshift and Aurora. The role also involves compliance, data migration, production support, troubleshooting, and adapting solutions to evolving business requirements.

Designs and defines data platform architecture, data models, storage, and system integrations using Snowflake. Collaborates with integration and data architects, leads cross-team decisions, facilitates stakeholder workshops, provides enterprise-wide solutions, and mentors junior professionals. Responsibilities include Snowflake schema design, performance tuning, query optimization, ETL and data integration, database management, cloud architecture, scalability, and security.

Designs and maintains data models across conceptual, logical, and physical stages. Partners with clients, integration architects, and data architects to understand requirements, conduct discovery workshops, create solution blueprints, and secure deliverable sign-off. Develops dimensional, 3NF, and NoSQL models, supports cloud database and modern data platform design, and provides DDL scripts to data engineers. Responsibilities also include estimation, technical solutioning, data warehouse and analytics project support, and client presentations.

Designs and leads graph data solutions, including graph databases, data models, integration patterns, and scalable ETL pipelines. Collaborates with Integration and Data Architects to develop cohesive data platforms, optimize graph ingestion and query performance, and deliver architecture documentation for approval. The role requires expertise with Neo4j, TigerGraph, AWS Neptune, graph query languages, data transformation, analytics projects, and programming in Python, Scala, or SQL.

Designs and supports data platform blueprints and components, collaborating with integration and data architects to align systems and data models. Provides database design, optimization, integration, troubleshooting, and architecture solutions. Serves as a subject matter expert, manages team performance and decisions, supports multiple teams, and facilitates knowledge sharing.

Build, maintain, and optimize scalable batch and real-time data pipelines using Python, PySpark, Spark, and cloud platforms. Develop ETL/ELT processes, data ingestion strategies, data lakes, and Big Data frameworks. Collaborate with architects, analysts, data scientists, and engineers to ensure data accuracy and availability. Support streaming workloads, Spark performance tuning, governance, security, orchestration, and CI/CD practices across cloud environments.

Designs and implements scalable data platforms, ETL/ELT pipelines, cloud infrastructure, data warehouses, and batch or real-time processing systems. Profiles customer data, improves performance, and ensures data quality, governance, compliance, and documentation. Collaborates with integration and data architects while delivering structured data assets for AI/ML and business intelligence teams. The role requires expertise in Python, SQL, Spark or Databricks, orchestration, streaming technologies, and modern data storage formats.

Develop and support scalable AWS data platforms and end-to-end ETL pipelines using AWS Glue, Lambda, Python, and PySpark. Collaborate with integration and data architects on platform blueprints, data models, and system integration. Work with SQL, Redshift, Aurora, GitLab CI/CD, CloudFormation, cloud infrastructure, compliance best practices, code migration, deployment, and production support.