Looking for a Data Engineer from India for our Enterprise Client
Budget: $20 – $25 USD
Looking for a Data Engineer from India for our Enterprise Client (INDIVIDUALS ONLY). Teams/Enterprises/Consultancies/Agencies please stay away.
Project Duration: 3-6 months
Location: Remote/WFH
Hours Required: 40 hrs/week
Responsibilities
• Diverse Data Engineering activities using best of the breed commercial and in-house platforms both cloud and on-premise solutions
• Build & Deliver Data pipeline connecting various enterprise data sources both RDBMS, NoSQL & APIs to process structured, semi-structured and unstructured data
• Develop data mappings to existing data sources, Lead the data identification, data analysis efforts for data sources and work directly with data owner teams
• Design and development of data extraction, data ingestion, data quality rules implementation
• Evaluate and define functional requirements for BI, DW, and Big Data solutions
• Involvement in architecture and design of data of BI, DW, and Big Data solutions
• Clean and process the data for Machine Learning consumption
• Support by leveraging project standards and leading data consumption by analytics platforms
Required Skills
• Lead the data identification, data analysis efforts for data sources and work directly with data owner teams
• Develop data requirements for new data sources.
• Define new business data models.
• Good knowledge of Database concepts, SQL and experience in working with Database clients like, TOAD, SQL developer, SQL Server Management Studio
• Good knowledge of NoSQL/ Document DB.
• Good understanding of Enterprise Information Model and Expertise in data modeling in Data Warehouse environment, with in-depth knowledge of Data Modeling concepts
• Proficient in analyzing business requirements and mapping them to technical requirements
• Good exposure to Enterprise Data Architecture, Data Quality Management, ETL mapping, data classification, operational system design
• Data Analysis and Interpretation, and Data Issue Debugging Skills
• Understanding data integration (ETL) processes is a plus
• Experience with Big Data and cloud-based data platforms (Azure or AWS)
• Experience with Azure Data Factory, ADLS, Databricks, Python & PySpark, Azure Functions, Logic Apps, SQL
• Able to understand technical issues and translate them into business problems
• Knowledge of working in a Cloud-based environment on Azure and AWS will be a big plus
Project Duration: 3-6 months
Location: Remote/WFH
Hours Required: 40 hrs/week
Responsibilities
• Diverse Data Engineering activities using best of the breed commercial and in-house platforms both cloud and on-premise solutions
• Build & Deliver Data pipeline connecting various enterprise data sources both RDBMS, NoSQL & APIs to process structured, semi-structured and unstructured data
• Develop data mappings to existing data sources, Lead the data identification, data analysis efforts for data sources and work directly with data owner teams
• Design and development of data extraction, data ingestion, data quality rules implementation
• Evaluate and define functional requirements for BI, DW, and Big Data solutions
• Involvement in architecture and design of data of BI, DW, and Big Data solutions
• Clean and process the data for Machine Learning consumption
• Support by leveraging project standards and leading data consumption by analytics platforms
Required Skills
• Lead the data identification, data analysis efforts for data sources and work directly with data owner teams
• Develop data requirements for new data sources.
• Define new business data models.
• Good knowledge of Database concepts, SQL and experience in working with Database clients like, TOAD, SQL developer, SQL Server Management Studio
• Good knowledge of NoSQL/ Document DB.
• Good understanding of Enterprise Information Model and Expertise in data modeling in Data Warehouse environment, with in-depth knowledge of Data Modeling concepts
• Proficient in analyzing business requirements and mapping them to technical requirements
• Good exposure to Enterprise Data Architecture, Data Quality Management, ETL mapping, data classification, operational system design
• Data Analysis and Interpretation, and Data Issue Debugging Skills
• Understanding data integration (ETL) processes is a plus
• Experience with Big Data and cloud-based data platforms (Azure or AWS)
• Experience with Azure Data Factory, ADLS, Databricks, Python & PySpark, Azure Functions, Logic Apps, SQL
• Able to understand technical issues and translate them into business problems
• Knowledge of working in a Cloud-based environment on Azure and AWS will be a big plus