<div>At SRIM Works, we are at the forefront of technological innovation, transforming enterprises, businesses, and industries around the world.</div><div>As a dynamic multinational technology services company, we specialize in developing cutting-edge products, platforms, and solutions. Our comprehensive expertise encompasses Data &amp; Artificial Intelligence (Data/AI), Engineering Research &amp; Development (ER&amp;D), and Digital Product Engineering Services (PES). By leveraging these capabilities, we drive the future of technological advancements, ensuring our clients stay ahead in an ever-evolving digital landscape.</div><div>Our commitment to excellence and innovation empowers businesses to achieve new heights, making SRIM Works a trusted partner in navigating the complexities of the modern technological world.</div>

SRIM WORKS

<div><strong>Job Description</strong></div><div>As 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.</div><div>&nbsp;</div><div><span style="color: rgb(32, 33, 36);">Practical experience delivering and supporting Cloud strategies including migrating legacy data and implementing SaaS integrations</span></div><div><span style="color: rgb(32, 33, 36);">&nbsp;</span></div><div><span style="color: rgb(32, 33, 36);">Specialist understanding and experience of methodologies like data warehousing, data visualization and data integration</span></div><div><span style="color: rgb(32, 33, 36);">&nbsp;</span></div><div><span style="color: rgb(32, 33, 36);">Strong experience with relational database technologies (SQL &amp; No SQL), preferably Data Lakehouse technologies like Databricks platform </span></div><div><strong>&nbsp;</strong></div><div><strong>&nbsp;</strong></div><div><strong>Responsibilities</strong></div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Design, develop and maintain optimal data pipelines.</div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Analyze and organize raw data.</div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Work closely with product managers and engineering managers to translate their needs into ETL flows.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Assemble large, complex data sets including legacy structured data warehouse that meet functional / non-functional business requirements.</div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;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.</div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Participate in data modelling discussion and influence the data architecture to ensure the best performance for solutions required by various teams.</div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Solve Big Data and Distributed Data Streaming problems using latest technologies.</div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Managing globally distributed data.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Manipulate, process and extract value from large, disconnected datasets.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Build processes supporting data transformation, data structures, metadata, dependency and workload management.</div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Implement best practices to enhance data quality and reliability.</div><div style="text-align: justify;">·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Identify opportunities for data acquisition.</div><div><strong>&nbsp;</strong></div><div><strong>&nbsp;</strong></div><div><strong>Requirements</strong></div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Bachelor’s degree in Computer Science or related field</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Expertise in setting up effective pipelines to capture data from multiple sources into the enterprise centric storage.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;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.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Possess strong knowledge in designing database models to store structured &amp; unstructured data efficiently and in creating effective data tools for analytics experts.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Working knowledge in relational model databases (like MSSQL, MySQL, Oracle etc.) and no-SQL databases (Azure cosmos DB, MongoDB, Elastic Search etc.)</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Knowledge on enterprise data lakes, data analytics, reporting, in-memory data handling, enterprise integration tools, etc.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience in defining and setting up data architecture to support warehousing and BI.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience working with Big Data technologies on Azure cloud platform including Azure Databricks and Azure Data Factory.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Having an owner's mindset and experience working in a fast-paced and demanding environment.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience in technologies like Hadoop, Spark, Scala, Python, etc. is a plus.</div><div>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Additionally high availability / recovery strategies (design implementation and management)</div>