Senior Software Engineer
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SMC Squared provides US companies with IT talent to accelerate innovation, develop digital products and services, or simply get basic operational work done. Our GIC approach helps CIOs minimize risk and cost and also improve quality and retention. Whether clients need a small team of 5 developers or 500 engineers in a dedicated facility, our employee-based approach builds dedicated teams of top technology talent with the same mission, vision, and values as their US counterparts. We recruit-for-fit rather than assign-for-need, thus creating a common culture, establishing stronger control, and radically improving resource retention. Our leadership team has walked in your shoes and worked alongside talent in the US and India for more than 70 collective years. We bring a people-first approach and respect that attracts and retains high quality Bangalore-based talent.
Job ID: 114432333
Skills:
.NET, Java, C, Waterfall, Jsp, J2EE, Sql, HTML, Javascript, Data Manipulation Language, Agile, Xml, data storage subsystems, test-driven development, normalized dimensional data modeling
Skills:
Ssms, T-sql, Tfs, VB.NET, Ssrs, CSS, Ms Sql Server, Visual Studio, SSIS, HTML, jQuery, Git, Javascript, Classic Asp
Skills:
Odata, Visual Studio, Data Factory, Github, Ssrs, Azure Logic Apps, Power Bi, Aif, Python, Sql Server Management Studio, Service Bus, MS Fabric, AI Builder, Microsoft Fabric, Copilot Studio, Dual Write, DMF, DevOps pipelines, Integration strategies, SOAP APIs, Common Data Services, ETL techniques, D365 Extension framework
Skills:
data engineering , data vault , Sql, S3, ELT, Emr, Data Warehousing, Dimensional Modeling, Apache Spark, Kinesis, Kafka, Etl, AWS, Python, Git, Data Modeling, Apache Hudi, Athena, Airflow, Flink, Delta Lake, Infrastructure as Code, Glue, Apache Iceberg
Skills:
data discovery , Google Cloud Platform, Kafka, Data Modeling, Data Lineage, Sql, Metadata Management, Python, Data lakehouse principles, Parquet, cdc, SCDs, Streaming architectures, Google BigQuery, Dimensional models, Pub Sub, AI ML use cases, Google Cloud Storage, Data pipelines, Data versioning
