Data Engineer in Pune

DeepIntent is leading the healthcare advertising industry with data-driven solutions built for the future

Burckhardt Compression looks for a +10y experience Data Engineer

Work on engaging projects with the largest international and local banks, insurance companies, payment service providers, and other key players in the industry

Barclays is seeking a Senior ETL Developer in Pune, Maharashtra, to design and improve high-quality software solutions using ETL technologies, particularly Ab Initio. The role involves cross-functional collaboration, code quality assurance, and adherence to secure coding practices, with an emphasis on automation and performance optimization

Responsible for supporting the successful delivery of location strategy projects with a focus on planning, budgeting, and governance standards

Work with a cross-functional and geographically dispersed team for quality assurance

Support the bank's decision-making processes by providing timely, accurate, and insightful information through designing, developing, and maintaining management reports, compelling visualisations and dashboards

** Brightonparkbank is seeking a Data Analytics & BI Engineer in Pune, Maharashtra, to enhance decision-making processes through the design and development of management reports, dashboards, and data visualizations. The ideal candidate should have strong BI engineering capabilities, experience with SQL and data modeling, and proficiency in BI tools such as Power BI or Tableau. **

Spearhead the evolution of infrastructure and deployment pipelines, driving innovation and operational excellence

** Brightonparkbank is seeking a Data Engineer specializing in Abinitio to develop and maintain data architectures, including pipelines, warehouses, and lakes, to ensure accurate and secure data management. The ideal candidate should possess strong technical skills, particularly in Python, Spark, and SQL, and demonstrate leadership capabilities if in a supervisory role. **

Citi is seeking a Senior Big Data Engineer to design and optimize large-scale data pipelines in a hybrid work environment based in Pune, India. The role requires expertise in PySpark, the Hadoop ecosystem, and complex SQL, with a focus on supporting business intelligence through effective data management

Join a team focused on building robust, scalable, and efficient data infrastructure

Join a team focused on building robust, scalable, and efficient data infrastructure

** Syngenta Group is seeking a Data Engineer for its HR organization in Pune, India. The role involves designing and maintaining scalable data pipelines and ensuring data quality for analytics and data science initiatives. **

Support the design and development of data foundations that power analytics and data science initiatives within Syngenta’s HR organization

The role involves formulating system scope and analyzing business client needs to drive technology innovations for global banking

The role involves designing and building scalable data pipelines using PySpark to process large volumes of structured and unstructured data

The role involves developing scalable data pipelines and warehouses to enable a science-driven people function within Medline

The role involves leveraging deep technical knowledge to drive the creation of high-quality data products for business decision-making

The role involves formulating system scope, analyzing client needs, and assessing risk within a global banking environment

The role involves participating in the establishment and implementation of new or revised application systems within the Technology team

The role involves designing and building scalable data pipelines using PySpark to process large volumes of structured and unstructured data

The role involves formulating system scope and analyzing business client needs to document requirements for big data solutions

The role involves building an A-team of highly skilled engineers focused on creating robust, end-to-end data solutions from ingestion to consumption

The role involves designing and building scalable data pipelines using PySpark to process large volumes of structured and unstructured data