data engineering , data warehouses , Cloud Infrastructure, Data Quality, Etl, ELT, IAM permissions, Orchestration tool like Airflow, GCP services

Pyspark, Github, Hadoop, JIRA, Sql, Hive, Bitbucket, Spark, Databricks, Workday Studio, Azure, AWS, Salesforce

Java, Spark SQL, Hadoop Ecosystem, Scala, Apache Spark, Data Warehousing Concepts, Sql, Hive, Data Modelling, Python, tests and deployments, HDFS, Pipeline-as-code, DataFrames, Automated builds

Pyspark, Azure Databricks, Sql, Clusters, Kubernetes, Python, RBAC configuration, Ability to debug and optimize PySpark SQL code, Programming Data Processing using Scala, Databricks Platform Expertise, Unity Catalog, Azure Services, Experience in AWS using Docker, CI CD with Azure DevOps, Jobs, Secure Coding principles in Databricks, Blob Storage, Data Governance and Compliance standards, Notebooks, Delta Lake, Apache Spark optimization techniques, Helm framework

Spark SQL, BigQuery, Hadoop, Scala, Apache Spark, Kafka, Dataproc, Sql, Hive, Gcp, Python, Airflow, Pub Sub, Cloud Composer, Google Cloud Storage

snowflake , Terraform, Azure, Sql, Python, AWS, Airflow, Dagster, dbt

Azure Data Factory, Pyspark, Azure Synapse Analytics, Azure Databricks, Python, Sql, Azure Data Lake Storage

snowflake , Pyspark, Rdf, Neo4j, Python, BigQuery, Apache Spark, Sql, Databricks, Airflow, GraphDB, pgvector, SHACL, Great Expectations, Pinecone, Flink, Cypher, AWS Glue DataBrew, Chroma, owl, Stardog, ShEx, Dagster, dbt, Milvus, Weaviate, Apache Jena

data quality assurance , Data Modelling, Data Warehousing, Python, Sql, Data Integration, Database Design, ETL processes, Cognite Data Fusion

Data Modeling, Pyspark, Apache Spark, Python, Sql, Etl, ELT, Batch Streaming Pipelines, Data Lakehouse Concepts, Distributed Data Processing