We're on the lookout for exceptional individuals to join our team as
Principal Data Engineers
. As a part of our team, you'll be driving change and making a significant impact in the gaming industry.
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Lead the design, development, and maintenance of end-to-end data analytical solutions using Microsoft on-premises and cloud technologies.
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Engage in collaborative requirement elicitation activities with our valued clientele.
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Mentor and guide junior team members in the field of data engineering.
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Showcase your expertise by delivering innovative analytical solutions to our clients and contributing to knowledge transfer within the organization.
Requirements
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6+ years of experience as a data engineer.
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Familiarity with analytical architectures including Data Warehouses, Data Lakes and Data Lakehouses.
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Knowledge of Microsoft relational engines available - both on-premises (MS SQL Server) and on the cloud (Azure SQL, Azure Synapse Analytics Dedicated Pools).
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Knowledge of query and workload optimization.
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Knowledge of administrating and managing analytical solutions both on premises and on the cloud.
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Knowledge of NoSQL offerings on Azure (e.g. CosmosDB).
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Knowledge of setting up Data Lakes on ADLS gen 2 and Azure Synapse Analytics.
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Knowledge of using SSIS and Azure Data Factory to set up ETL jobs.
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Knowledge of setting up OLAP solutions using SSAS.
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Familiarity with Azure Data Catalog to manage data lake metadata.
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Knowledge of governance over Azure based analytical solutions including using tools such as Purview, Active Directory, Key Vault, Azure DevOps, etc.
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Knowledge of using Azure Stream Analytics to capture and analyze data in real time.
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Knowledge of setting up data warehouse solutions both on-premises (using MS SQL Server) and on the cloud (using Azure Synapse Analytics).
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Knowledge of Dimensional Modeling (Dimensions, Facts, Slowly Changing Dimensions, Outriggers, Role Playing Dimensions, Junk Dimensions, Degenerate Dimensions, Multi-valued Dimensions, Transactional Facts, Periodic Snapshot Facts and Accumulating Snapshot Facts).
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Knowledge of implementing common ETL patterns to support data warehouse workloads.
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Knowledge of using U-SQL, PolyBase and Azure Data Lake Analytics to perform federated querying.
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Knowledge of PowerBI.
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Familiarity with SSRS.
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Snowflake Experience:
Experience with Snowflake is required.
Nice to Have:
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An MSc in Computer Science or other relevant field.
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Familiarity with Azure Databricks.
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Familiarity with DataOps
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Familiarity with Azure Cognitive Services.
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Familiarity with Azure ML.
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Familiarity with MLOps.
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Familiarity of containerization tools and frameworks (Docker, Kubernetes, etc.)
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Familiarity with Azure HD Insight.
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Familiarity with the Hadoop ecosystems, including tools like Hive, Spark and Kafka.
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Familiarity with Azure Functions to perform lightweight transformations.
Benefits
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Salary paid in USD
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Six-month career advancing opportunities
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Supportive and friendly work environment
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Premium medical insurance [employee +family]
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English language development courses
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Interest-free loans paid over 2.5 years
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Technical development courses
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Planned overtime program (POP)
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Employment referral program
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Premium location in Maadi
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Social insurance