Top Data Engineer Jobs in Bangalore

Design, develop, and support enterprise data platforms, ETL/ELT pipelines, Oracle databases, data warehouses, and risk and regulatory reporting solutions. Build automation, optimize SQL and data processing, ensure data quality, reconciliation, lineage, governance, and audit readiness. Provide L2/L3 production support, resolve incidents, manage batch operations, and perform root-cause analysis. Collaborate with Risk, Finance, Regulatory, Business, and Technology stakeholders while mentoring junior team members.

Designs and supports enterprise data platforms, ETL/ELT pipelines, Oracle databases, data warehouses, and risk and regulatory reporting solutions. Responsibilities include SQL/PLSQL development, data integration, quality, reconciliation, governance, production support, incident resolution, automation, batch scheduling, and regulatory reporting. The role partners with Risk, Finance, Compliance, Business, and Technology stakeholders while providing technical leadership and mentoring.

Designs and refines data platform blueprints, collaborates with integration and data architects, and leads implementation of scalable, interoperable platform strategies. The role oversees platform optimization, supports data visualization solutions, translates complex datasets into actionable insights, coordinates decisions across teams, and promotes knowledge sharing and continuous improvement.

Designs and refines data platform blueprints, collaborates with integration and data architects, and supports cohesive system and data model integration. The role contributes to data platform solutions, identifies architecture improvements, supports automation and data workflows, and aligns platform components with business needs. It requires Databricks expertise, data integration and transformation experience, cloud data platform knowledge, data modeling skills, and the ability to work independently as a subject matter expert while mentoring junior team members.

Contributes to the design and refinement of data platform blueprints and components. Collaborates with integration and data architects to ensure cohesive system integration and consistent data models. Develops solutions, identifies platform optimizations, supports data integration and transformation, and applies cloud platform, scripting, and automation knowledge. Works independently as a subject matter expert, participates in team discussions, and guides junior team members.

Designs and refines data platform blueprints, collaborates with integration and data architects, and supports cohesive system and data model integration. The engineer identifies platform improvements, contributes solutions, participates in technical discussions, aligns components with business needs, and guides junior team members. The role requires Databricks expertise, data integration and transformation experience, cloud data platform knowledge, data modeling, and scripting or automation skills.

Designs and refines data platform blueprints, collaborating with integration and data architects to align systems, data models, and platform components. Supports data integration, transformation, automation, optimization, and architecture improvements in large-scale cloud data environments. Works independently as a subject matter expert, contributes solutions, participates in team discussions, and guides junior team members. Requires Databricks expertise and strong understanding of data modeling and cloud data platforms.

Develops and refines data platform blueprints and designs, integrating platform components across systems and data models. Collaborates with architects and cross-functional teams, identifies platform improvements, supports data integration and transformation, and provides technical guidance to junior team members. The role requires Databricks expertise, cloud data platform knowledge, data modeling, and scripting or automation skills.

Contributes to the design and refinement of data platform blueprints, collaborating with integration and data architects to align platform components, systems, and data models. Supports data integration, transformation, workflow automation, platform optimization, and architecture strategy. Works independently toward subject-matter expertise, contributes to team solutions, and mentors junior team members.

Contributes to the design and refinement of data platform blueprints, collaborating with integration and data architects to align systems, data models, and platform components. Develops data integration and transformation solutions in large-scale environments, supports cloud-based platform operations, identifies architecture improvements, and automates workflows. Works independently as a subject matter expert, contributes to team discussions, solves technical problems, and guides junior team members.

Designs and maintains scalable data pipelines and enterprise data platforms using Azure Data Factory, ADLS, Databricks, PySpark, Python, and SQL. Builds Energy Trading and Risk Management solutions leveraging Endur and Nucleus, develops data models, tunes performance, and supports analytics and reporting. The role also manages CI/CD and release processes, data governance, MDM, data catalogs, and Agile delivery while partnering with business and technical stakeholders on trading data solutions.

Build and operate production data pipelines across ingestion, transformation, orchestration, quality, and delivery using Azure Databricks, dbt, Airflow, and Azure Data Factory. Develop trusted data products using data mesh principles, optimize platform performance and costs, and implement testing, monitoring, CI/CD, and infrastructure automation. Partner with business, platform, and AI teams to translate requirements into scalable solutions and communicate technical trade-offs.

Designs and maintains ETL/ELT pipelines using Informatica IICS and Snowflake. Develops mappings, taskflows, stored procedures, and data-loading strategies including CDC and SCD patterns. Builds scalable data warehouse solutions, performs data transformation and validation, troubleshoots failures and performance issues, and supports production deployments. Collaborates with business analysts, architects, QA, and technical teams. Preferred experience includes cloud services, storage platforms, CI/CD, scripting, version control, and life sciences or pharmaceutical domains.

Design, build, and maintain scalable, fault-tolerant batch and streaming data pipelines and a petabyte-scale data warehouse. Own data mapping, transformations, quality, performance tuning, and support of production big-data platforms while collaborating with cross-functional teams and influencing architecture and roadmap.

Designs and maintains scalable cloud-based data infrastructure, ingestion architectures, ETL pipelines, data lakes, warehouses, and analytical platforms. The role involves SQL and PySpark development, data quality and performance troubleshooting, automated testing, streaming and API validation, DevOps integration, documentation, and collaboration with data scientists, analysts, and global stakeholders. The engineer also applies data warehousing, governance, dimensional modeling, and emerging AI technology knowledge.

Manage business-as-usual data engineering for consumer and commercial bureau operations. Analyze large datasets to identify insights and solve entity resolution challenges through keying and linking. Design and develop solutions on GCP and Ignite, support dashboards and metrics, gather requirements, and communicate findings to technical and business stakeholders. Lead small or mid-sized teams while collaborating cross-functionally.

Manage business-as-usual data engineering for consumer and commercial credit bureau operations. Analyze large datasets, identify insights, and apply entity resolution techniques to solve keying and linking problems. Design and develop solutions on GCP and Ignite, create metrics, dashboards, presentations, and analyses, gather requirements, and support cross-functional stakeholders. The role also involves managing small to mid-size teams and communicating technical findings to technical and non-technical leaders.

Design, develop, and deploy Tableau dashboards and BI solutions. Build and automate ETL/data pipelines, transform and model data for warehousing, publish to Tableau Server, and collaborate with stakeholders. Provide technical architecture, documentation, and lead teams on multiple large Agile projects while mentoring engineers and ensuring data quality and performance.

Design and refine the enterprise data platform blueprint, collaborate with Integration and Data Architects, lead and mentor the team, ensure system interoperability and data integrity, implement platform improvements, and provide analytics-driven solutions across teams.

Lead design and optimization of enterprise data platform blueprint and components, collaborate with Integration and Data Architects, enforce data governance using Collibra, mentor team, resolve cross-team platform issues, and ensure scalable, interoperable data solutions.

Build and enhance enterprise data pipelines into Databricks Unity Catalog and Delta Lake. Improve remediation and entity-matching layers (including D&B DataBlocks), integrate APIs, and support LLM-assisted remediation and CMG redesign projects.

Design, build, and optimize Azure-based ETL/ELT pipelines using PySpark and Spark SQL on Databricks. Orchestrate workflows (ADF/Airflow), implement hybrid integrations, enforce data quality and governance, support CI/CD, troubleshoot pipeline issues, and collaborate with analysts and data scientists.

Design and deliver end-to-end analytics and application solutions: build data pipelines, backend services, APIs, dashboards, and web portals using SQL, Python, cloud (AWS), and modern frontend stacks. Partner with stakeholders to translate business needs into scalable, secure production systems, apply GenAI/LLM tools to accelerate delivery, and provide production support, mentoring, and continuous improvement.

Design, develop, and maintain global operational dashboards and reports, ensure master data accuracy across ERP/MES/CRM systems, support data governance, identify supply chain performance trends, and enable scalable analytics solutions to improve efficiency and reduce cost.

Develop and maintain reporting, analytics, and visualizations (Power BI) to support PSI processes. Automate KPI distribution, measure forecast accuracy, analyze deviations, and partner with demand, supply, finance, and sales to enable data-driven supply chain decisions.