data pipelines, Databricks Unified Data Analytics Platform, ETL processes, data integration techniques, scripting and automation, cloud-based data storage and processing solutions

snowflake , Sql, Python, Snowpark, Relational Databases, Big-data platforms

Adf, Pyspark, Data Modeling, Azure Data Lake, Scala, Apache Spark, Sql, MLops, Data Governance, Databricks, Aws S3, Airflow, workflow orchestration tools, MLflow, CI CD, DBX Workflows, Lakehouse architecture, Cataloging, Git-based workflows, DevOps practices, security frameworks, GCP BigQuery Storage, ETL frameworks, Delta Lake

Servicenow, Apache Airflow, Cloud Storage, Confluence, Terraform, Python, BigQuery, Jira, Jenkins, Gcp, Iam, Gitlab, DataFlow, Cloud Spanner, Data Ingestion, CI CD, Pub Sub, Cloud Composer, Workbench Instances, Vertex AI, Cloud SQL for PostgreSQL, Reverse ETL, GCP Monitoring and Alerting, dbt, Artifact Registry, Eventarc, GCP Networking, Secret Manager, Pentaho

Pyspark, PostgreSQL, AWS Glue, Nosql, Numpy, Terraform, Python, AWS, Pyspark, Cloudformation, Dynamodb, Data Architecture, Sql, Pandas, Aws Cli, Amazon Redshift, Apache Kafka, Databricks, Kubernetes, Airflow, AWS CDK, Dask, dbt, Modern data processing frameworks, Iceberg, Cloud-native solutions, Data lake architectures, Delta Lake

snowflake , Adf, Pyspark, Scala, Data Warehouse, Sql, Spark, Data Lake, Databricks, Azure, Python, Delta Table, Synapse, ADLS

snowflake , BigQuery, Api Integration, Redshift, Sql, ELT, Gcp, Rest Apis, Azure, Etl, AWS, data pipelines, dbt

data engineering , Technical Documentation, Cloudera, scalable data pipelines, secure data processing, data platforms, monitoring observability