[Hiring] Data Engineering Lead @Srim Works

Role Description

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.

• 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

• 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.

Qualifications

• 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)