Top Data Engineer Jobs in Bangalore

The IT Engineer Tech Lead will govern data acquisition architecture, establish reusable interfaces, define standards, and support data engineering teams across multiple sources, ensuring quality integration and analytics.

The IT engineer will design and develop scalable data pipelines in Azure Databricks, ensuring data quality and availability for HR, Purchasing, and Finance. Key tasks include implementing ingestion from various sources, developing modular code, and collaborating across teams to refine user stories and align with governance standards.

The IT engineer will design and develop data pipelines in Azure Databricks, ensuring data quality for Sales & Finance. Responsibilities include implementing data architectures, collaborating with stakeholders, and applying agile methodologies.

Design and optimize ETL/ELT pipelines using Azure technologies, develop complex SQL solutions, and streamline data lifecycle automation while ensuring production reliability and compliance.

Lead Data Engineer responsible for advanced AWS Data Engineering focusing on various tools and technologies, including Athena, Spark, DynamoDB, and more.

The Senior Data Engineer role involves data mapping, ETL process development, and collaboration with stakeholders to deliver high-quality data solutions.

The role involves designing and building data engineering solutions, developing data pipelines, ensuring data quality, and collaborating with teams to enhance data accessibility and decision making.

The Senior Data Analytics Engineer at MariaDB designs and builds data pipelines, writes SQL queries, develops internal tools, and translates data into actionable insights. They will collaborate closely with stakeholders and leverage AI tools to enhance analytics workflows.

Design, build, and maintain scalable cloud data platforms and ETL/ELT pipelines using AWS (Glue, Lambda, Redshift, S3) and Python/PySpark. Implement data warehousing, modeling, governance, monitoring, and performance optimization. Collaborate with stakeholders, mentor junior engineers, support production deployments, and drive cloud modernization and best practices to enable analytics and ML initiatives.

The job involves designing and maintaining data pipelines, building data models, creating dashboards for IT performance insights, collaborating with stakeholders, ensuring data quality, and keeping up with new technologies.

Design and implement scalable data pipelines using Databricks and Apache Spark. Optimize lakehouse architectures and ensure data quality and governance. Collaborate with stakeholders for effective data solutions.

As a Senior Data Engineer at Roku, you will design scalable data models, develop data pipelines, and optimize existing datasets to enhance business metrics and support a big data platform.

Lead the design and maintenance of complex SQL solutions, overseeing ETL processes and ensuring data accuracy for enterprise operations while mentoring data engineers.

The Senior Data Engineer will design and optimize ETL/ELT pipelines, manage data integration, perform data validation, and support reporting solutions using various technologies.

The role involves designing, building, and operating analytics pipelines on Google Cloud Platform, utilizing modern practices for orchestration, transformation, and machine learning integration.

The Senior Data Engineer will design and maintain scalable data pipelines, developing ELT/ETL workflows and collaborating with various teams for supply chain analytics and customer collaboration.

The Lead Data Engineer is responsible for building and maintaining ELT/ETL data pipelines, collaborating with teams to fulfill data transformation and reporting requirements, and improving data reliability and quality while mentoring others in best practices.

The Lead Data Engineer designs and optimizes data pipelines, develops data solutions, collaborates with teams, and applies best practices in data engineering.

Oversee the scheduling, monitoring, and delivery of client reports, ensuring secure and timely delivery, while managing automation workflows and responding to reporting requests.

The Support Engineer will optimize machine learning techniques, conduct data mining, handle forecasting issues, and enhance datasets while collaborating closely with engineering and product teams.

The Senior Data Scientist & Engineer will build and manage data infrastructure, analyze product usage, build models, track metrics, run experiments, and communicate insights to guide product decisions.

The role involves utilizing advanced technical knowledge to solve challenges while guiding teams and enhancing client solutions. Emphasis is on collaboration and extending beyond traditional coding tasks.

Design, build, and productionize end-to-end cloud data solutions and pipelines for enterprise clients. Translate business needs into technical architectures, ensure performance, security, and scalability, lead technical reviews, produce documentation and runbooks, mentor peers, and collaborate with client and cross-functional teams to deliver consulting engagements on time and with measurable value.

Design, build, and maintain scalable batch and real-time data pipelines and platforms to ensure data quality, availability, and AI-readiness. Support analytics and Generative AI workloads, enable feature stores and embeddings, monitor pipeline performance, resolve data issues, and implement validation, documentation, and lineage standards while collaborating with AI, analytics, and product teams.

Lead end-to-end customer data integration and migration projects using SQL, ETL, and scripting. Act as technical advisor, design tailored solutions, manage 10–15 projects, document requirements, mentor juniors, and collaborate with government stakeholders and cross-functional teams to improve and automate data workflows.