8.0 - 12.0 years

0 Lacs

karnataka

On-site

Working with data on a day-to-day basis excites you, and you are interested in building robust data architecture to identify data patterns and optimize data consumption for customers who will forecast and predict actions based on data. If this excites you, then working in our intelligent automation team at Schneider AI Hub is the perfect fit for you. As a Lead Data Engineer at Schneider AI Hub, you will play a crucial role in the AI transformation of Schneider Electric by developing AI-powered solutions. Your responsibilities will include expanding and optimizing data and data pipeline architecture, ensuring optimal data flow and collection for cross-functional teams, and supporting software engineers, data analysts, and data scientists on data initiatives. You will be responsible for creating and maintaining optimal data pipeline architecture, designing the right schema to support functional requirements, and building production data pipelines from ingestion to consumption. Additionally, you will create preprocessing and postprocessing for various forms of data, develop data visualization and business intelligence tools, and implement internal process improvements for automating manual data processes. To qualify for this role, you should hold a bachelor's or master's degree in computer science, information technology, or other quantitative fields and have a minimum of 8 years of experience as a data engineer supporting large data transformation initiatives related to machine learning. Strong analytical skills, experience with Azure cloud services, ETLs using Spark, and proficiency in scripting languages like Python and Pyspark are essential requirements for this position. As a team player committed to the success of the team and projects, you will collaborate with various stakeholders to ensure data delivery architecture is consistent and secure across multiple data centers. Join us at Schneider Electric, where we create connected technologies that reshape industries, transform cities, and enrich lives, with a diverse and inclusive culture that values the contribution of every individual. If you are passionate about success and eager to contribute to cutting-edge projects, we invite you to be part of our dynamic team at Schneider Electric in Bangalore, India.,

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Data Analyst/Engineer I Capgemini Invent

6.0 - 10.0 years

0 Lacs

kolkata, west bengal

On-site

You must have knowledge in Azure Datalake, Azure function, Azure Databricks, Azure Data Factory, and PostgreSQL. Working knowledge in Azure DevOps and Git flow would be an added advantage. Alternatively, you should have working knowledge in AWS Kinesis, AWS EMR, AWS Glue, AWS RDS, AWS Athena, and AWS RedShift. Demonstrable expertise in working with timeseries data is essential. Experience in delivering data engineering/data science projects in Industry 4.0 is an added advantage. Knowledge of Palantir is required. You must possess strong problem-solving skills with a focus on sustainable and reusable development. Proficiency in using statistical computer languages like Python/PySpark, Pandas, Numpy, seaborn/matplotlib is necessary. Knowledge in Streamlit.io is a plus. Familiarity with Scala, GoLang, Java, and big data tools such as Hadoop, Spark, Kafka is beneficial. Experience with relational databases like Microsoft SQL Server, MySQL, PostGreSQL, Oracle, and NoSQL databases including Hadoop, Cassandra, MongoDB is expected. Proficiency in data pipeline and workflow management tools like Azkaban, Luigi, Airflow is required. Experience in building and optimizing big data pipelines, architectures, and data sets is crucial. You should possess strong analytical skills related to working with unstructured datasets. Provide innovative solutions to data engineering problems, document technology choices, and integration patterns. Apply best practices for project delivery with clean code. Demonstrate innovation and proactiveness in meeting project requirements. Reporting to: Director- Intelligent Insights and Data Strategy Travel: Must be willing to be deployed at client locations worldwide for long and short terms, flexible for shorter durations within India and abroad.,

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