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

Spark SQL, S3, RDS, Aws Services, Pyspark, Emr, Jenkins, Git, Devops Tools, Python, Big Data concepts, AWS architecture, AWS cloud microservices, cloud implementation projects, Aurora, Snowflake SQL, Glue, Data Vault 2.0

Sql Pl Sql, Document Databases Working knowledge of MongoDB, ETL Tools Proficiency in Ab Initio GDE EME Co Operating System, Unix Linux Scripting, Testing QA Exposure to SIT E2E and OAT testing cycles, Messaging Systems Experience with IBM MQ Apache Kafka, Scheduling Tools Familiarity with Tivoli Workload Scheduler TWS, Agile Delivery Experience with JIRA, Security Compliance Awareness of access control vulnerability assessments

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

Java, Scala, Apache Spark, Apache Kafka, Python

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