Data Engineering - Technology in Bengaluru, India - Jobeax
Vacancy description
Data Engineering - Technology in Bengaluru, India
ADM
India, Bengaluru
Data Engineering - Technology in Bengaluru, India is listed on Jobeax. Browse 30,000+ vacancies available.
About ADM: We are one of the world's largest nutrition companies and a global leader in human and animal nutrition. We unlock the power of nature to provide nourishing quality of life by transforming crops into ingredients and solutions for foods, beverages, supplements, livestock, aquaculture, and pets.
About ADM India Hub: At ADM, we have long recognized the strength and potential of India's talent pool, which is why we have maintained a presence in the country for more than 25 years. Building on this foundation, we have now established ADM India Hub, our first GCC in India. At ADM India Hub, we are hiring for IT and finance roles across diverse technology and business functions. We stand at the intersection of global expertise and local excellence, enabling us to drive innovation and support our larger purpose of unlocking the power of nature to enrich quality of life.
Senior Data Engineer Do you want to join a team passionate about engineering data solutions to inform business decisions and transform business performance ADM is seeking a Sr. Data Engineer, someone who thrives in an environment continuously integrating and deploying data products and analytics driving business value. Data Engineer is responsible for delivery, adherence to standards, and mentoring team members. Data Engineer collaborates with teams to ensure delivery and contributes to technical design and process improvements. Data Engineer is a team player who sees problems as challenges to be creatively solved in collaboration with other data engineers, data scientists, and business colleagues. The ideal candidate is a driven learner who develops and sharpens skills building data pipelines, transforming raw data into useful data systems, and optimizing the data delivery architecture.
Responsible to design, build, refactor, and maintain data pipelines using Microsoft Azure, SQL, Azure Data Factory, Azure Synapse, Databricks, Python, and PySpark to meet business requirements for reporting, analysis, and data science Responsible to teach, adhere to, and contribute to DataOps and MLOps standards and best practices to accelerate and continuously improve data system performance Responsible to design, and integrate fault tolerance and enhancements into data pipelines to improve quality and performance Responsible to lead and perform root cause analysis and solve problems using analytical and technical skills to optimize data delivery and reduce costs Responsible to mentor Data Engineers at all levels of experience
Advanced experience with Microsoft Azure, SQL, Azure Data Factory, Azure Synapse, Databricks, Python, PySpark, SAP Datasphere, Power BI, SSIS or other cloud-based data systems Advanced experience with Azure DevOps, GitHub, CI/CD Advanced experience with database storage systems such as cloud, relational, mainframe, data lake, and data warehouse Advanced experience building cloud ETL pipelines using code or ETL platforms utilizing database connections, APIs, or file-based Advanced experience with data warehousing concepts and agile methodology Advanced experience designing and coding data manipulations applying processing techniques to extract value from large, disconnected datasets Experienced presenting conceptual and technical improvements to influence decisions Continuous learning to upskill data engineering techniques and business acumen
Education and Experience:
Bachelor's or Master's degree in computer science, software engineering, information technology or equivalent combination of data engineering professional experience and education.
7+ years proven Data Engineering experience in a complex agile environment
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... management of data systems to support efficient data storage, processing, and utilization. - Collaborate Cross-Functionally: Work closely with product managers, engineering teams, data scientists, and other stakeholders to design and implement effective data integration and hand-off mechanisms. Facilitate seamless data flow and ...
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