Top Data Engineer Jobs in Pune

Deliver data engineering and analysis work using Python, PySpark, SQL and data platforms (Airflow, Trino, Hive). Produce LLD, coordinate offshore teams, follow Agile/Scrum, and work with container platforms (Linux, OpenShift, Kubernetes) and visualization (Superset). Banking domain experience is a plus.

The Senior Data Engineer will design and develop data solutions, build data pipelines, analyze processes for improvements, and mentor junior engineers.

Build and operate a scalable data platform: design and maintain ETL/ELT pipelines, Bronze/Silver/Gold data layers, data models and semantic layers, manage migrations and schema changes, ensure data quality/observability, enable analytics and future event-driven/recommendation systems, and use AI-assisted workflows to accelerate engineering.

Support electrical design, engineering, commissioning, and delivery of liquid-cooled data centre solutions: prepare layouts, SLDs, wiring diagrams, BOMs, perform load calculations, assist testing/FAT/SAT, troubleshoot commissioning issues, coordinate cross-functional teams, and ensure compliance with IEC/NEC/IEEE and company HSE standards.

The Senior Data Engineer builds and maintains data systems, ensuring data integrity and security. Responsibilities include designing data pipelines, collaborating with data scientists, and managing data architectures. The role emphasizes leadership and strategic contributions to the organization.

The Senior Data Engineer builds and maintains systems for data collection, storage, processing, and analysis, ensuring accuracy and security.

Design, build, and productionize end-to-end cloud data solutions and pipelines. Translate business needs into technical architectures, ensure performance, security, scalability, and reliability in production. Deliver client engagements on time, produce technical documentation and runbooks, present solutions to stakeholders, mentor peers, and contribute reusable assets and best practices across the firm.

Develop and support secure IoT software applications, APIs, and UIs; build dashboards, ETL/data workflows, and analytics; enable ML/AI capabilities; maintain and modernize legacy code hosted on AWS.

Data Engineer responsibilities include designing and building scalable data management systems, optimizing data pipelines, managing data warehouses, and ensuring data quality and compliance.

Design, build, test, and maintain backend applications, APIs, and ETL/ELT data pipelines. Perform data transformation, validation, statistical analysis, and optimize code, queries, and pipelines. Troubleshoot production issues, collaborate with cross-functional teams, participate in code reviews, and document architectures and data workflows.

Design, build, and maintain scalable ETL pipelines and Python data workflows. Perform statistical analysis, optimize queries and pipelines, clean and validate large datasets, troubleshoot failures, document solutions, and collaborate with cross-functional teams to deliver reliable data solutions and insights.

Build and prepare data pipelines: mapping, cleansing, transformation, integration, and wrangling using Python and SQL. Perform feature engineering for structured and unstructured data and support API and web app deployment for data products.

Build and maintain scalable ETL pipelines on GCP, transform large/disconnected datasets, automate and optimize data delivery, support stakeholders, and apply data engineering best practices including testing and release management.

Design, build, and maintain scalable ETL/ELT data pipelines on GCP/BigQuery using Python and Spark. Integrate systems (APIs, Oracle EBS), implement workflow orchestration, ensure data quality and security, monitor performance, and document processes while collaborating with analysts and business teams.

Design, build, and maintain scalable ETL/ELT pipelines and microservices for marketing and product data, ingesting from ad platforms (especially Meta Ads) and event systems. Enable campaign performance tracking, lead funnel analysis, attribution, and revenue reporting. Ensure data quality, observability, governance, and documentation while collaborating with marketing, growth, and analytics to deliver actionable datasets and drive business outcomes.

Data Engineer responsible for building and maintaining ETL pipelines, data processing workflows, and data platforms. Must have strong hands-on experience with Healthcare Revenue Cycle Management and understanding of healthcare data workflows. Role requires hybrid (onsite + offshore) work and immediate availability.

Design, build, and optimize Snowflake data models and dbt pipelines. Create Power BI reports and paginated RDLs with DAX and row-level security. Manage CI/CD with Azure DevOps, version control with Git, enforce data quality and governance, and optimize warehouse cost and performance while collaborating with business stakeholders.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Design, implement, and lead large-scale generative AI and ML systems (LLM fine-tuning, RAG, agents, Graph ML). Build REST APIs, deploy with Docker/Kubernetes, optimize big-data workflows, mentor engineers, and operate ML services on cloud platforms.

Design, build, and maintain Power BI dashboards and semantic data models using Power BI and Microsoft Fabric. Optimize performance, troubleshoot dataset and refresh issues, ensure governance and data accuracy, and collaborate with stakeholders to modernize analytics platforms.

The role involves building a centralized data lake on GCP, developing SPARK-powered data pipelines, ensuring data quality, and collaborating with cross-functional teams for advanced analytics and data models.

Design, build, and operate batch and real-time data ingestion and transformation pipelines. Develop platform components (storage, compute, pipelines), monitoring, alerting, and data-quality tooling. Diagnose production issues, participate in on-call rotations, and build AI-powered agents to automate engineering and operational tasks.

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.

As a Staff Data Platform Engineer, you will lead the design and development of data infrastructure, manage CI/CD processes, and implement observability for data pipelines.

As a Data Engineer, you'll build and monitor large-scale data pipelines, develop the DBT setup for data transformation and solve customer problems using your SQL skills.