Pl Sql, Microsoft Azure, Azure Databricks, Python, Sql, AI ML tools

Debugging, Pyspark, Data Warehousing, Sql, Data Analysis, Postgres SQL or similar RDBMS, Data modeling fundamentals, Performance optimization, Azure cloud ecosystem or equivalent cloud platforms, ETL pipelines

snowflake , Sql, ELT, Nosql, Docker, Gitlab, Databricks, Rest Apis, Kubernetes, Python, Azure DevOps, Etl, GitHub Actions, Microsoft Fabric

data discovery , Metadata Management, Kafka, Slas, Data Modeling, Python, Data Lineage, Google Cloud Platform, Sql, Query Optimization, Data Quality, Clustering, cdc, data pipelines, observability practices, dimensional models, Google BigQuery, data versioning, Pub Sub, data lakehouse principles, streaming architectures, Parquet, SCDs, AI ML use cases, SLOs, partitioning, Google Cloud Storage

Power Bi, Pyspark, Pl Sql, Azure Databricks, Data Architecture, Power Query, Sql, Git, Azure Data Factory, Azure Data Lake, Dax, Oracle, Python, Azure DevOps, Azure Fabric

C, Python, Production Systems, Manufacturing software test automation, Manufacturing analytics, Data pipelines, MES systems

BigQuery, DataFlow, Talend, Python, Sql, ELT, Etl, Pub Sub, dbt

Ml, Apis, Microservices, Enterprise Integration, Distributed Systems, Containers, Kubernetes, Python, GenAI, cloud-native architecture, infrastructure automation, Ai, CI CD, secure development, modern data platforms, observability

Device Drivers, C, Linux kernel, Networking, Embedded Linux, Debugging, Arm, Software Quality Assurance, Python, certification documentation, simulation-based development, advanced debugging tools, virtualized hardware environments, hardware software integration, BSPs, full software lifecycle execution, embedded software architecture, open-source software, platform-level software, x86 platforms, multicore architectures, DO-178C safety certification, real-time systems