Job Opportunity for Data Practice Lead (Permanent WFH)-Only Immediate joiners to apply

Job DescriptionAs a Data Engineering Lead, you play a vital role in building the right infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources. Ideal candidate must have at least 10 years of experience working around data management and analysis. Practical experience delivering and supporting Cloud strategies including migrating legacy data and implementing SaaS integrations Specialist understanding and experience of methodologies like data warehousing, data visualization and data integration Strong experience with relational database technologies (SQL & No SQL), preferably Data Lakehouse technologies like Databricks platform Responsibilities·       Design, develop and maintain optimal data pipelines.·       Analyze and organize raw data.·       Work closely with product managers and engineering managers to translate their needs into ETL flows.·       Assemble large, complex data sets including legacy structured data warehouse that meet functional / non-functional business requirements.·       Work with various big data platforms, databases, and systems such as Spark, Databricks, Azure cosmos DB, SQL Server, Azure Data Factory, other big data technologies like Azure data lakes.·       Participate in data modelling discussion and influence the data architecture to ensure the best performance for solutions required by various teams.·       Solve Big Data and Distributed Data Streaming problems using latest technologies.·       Managing globally distributed data.·       Manipulate, process and extract value from large, disconnected datasets.·       Build processes supporting data transformation, data structures, metadata, dependency and workload management.·       Implement best practices to enhance data quality and reliability.·       Identify opportunities for data acquisition.Requirements·       Bachelor’s degree in Computer Science or related field·       Expertise in setting up effective pipelines to capture data from multiple sources into the enterprise centric storage.·       Comfortable in building effective analytical tools that utilize the data pipeline to provide actionable insights into data synchronization and operational efficiency of the data repositories.·       Possess strong knowledge in designing database models to store structured & unstructured data efficiently and in creating effective data tools for analytics experts.·       Working knowledge in relational model databases (like MSSQL, MySQL, Oracle etc.) and no-SQL databases (Azure cosmos DB, MongoDB, Elastic Search etc.)·       Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.·       Knowledge on enterprise data lakes, data analytics, reporting, in-memory data handling, enterprise integration tools, etc.·       Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.·       Experience in defining and setting up data architecture to support warehousing and BI.·       Experience working with Big Data technologies on Azure cloud platform including Azure Databricks and Azure Data Factory.·       Having an owner's mindset and experience working in a fast-paced and demanding environment.·       Experience in technologies like Hadoop, Spark, Scala, Python, etc. is a plus.·       Additionally high availability / recovery strategies (design implementation and management)