Data Analyst/Engineer I Capgemini Invent

About Capgemini Invent

Job Description

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.,