Big Data Engineer II

GG10.2Role Value PropositionData Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. The role requires one to demonstrate Big Data, Engineering and Cloud expertise.It is an individual contributor role, expected to independently functionExperience5-8+ years of relevant experienceEducationBachelors degree in computer science, information technology or equivalent educational qualificationResponsibilities

Design, build, and maintain robust ETL/ELT pipelines on cloud(Azure) or on-prem to collect, ingest and store large volumes of structured and unstructured data for batch/real time processing Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, and performance Ensure data processing, quality, security, and compliance guidelines, policies and standards are followed Collaborate with multiple partners from Business, Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights)Technical Skills SQL, Python/Scala NoSql and distributed databases (Hbase, Cosmos DB) ETL pipleine development Big Data Frameworks : Apache Spark, Hadoop, Hive Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks Datawarehouses, data marts, data lakes Medallion architecture Performance tuning, optimization, and data quality validation Real-time and batch data processing , streaming pipelines with SparkCommunication skills, analytical skills, structured problem-solving skills.,Partner, Stakeholder engagement experienceGood To have DevOps practices: Git, AzureDevops, CI/CD pipelines Unix shell scripting, MongoDB, Nifi Exposure to Gen AI technology and tools