Senior Lead Data Engineer - Databricks

We're on the lookout for exceptional individuals to join our team as Lead Data Engineers. As a part of our team, you'll be driving change and making a significant impact in the gaming industry.

• Lead the design, development, and maintenance of end-to-end data analytical solutions using Microsoft on-premises and cloud technologies.
• Engage in collaborative requirement elicitation activities with our valued clientele.
• Mentor and guide junior team members in the field of data engineering.
• Showcase your expertise by delivering innovative analytical solutions to our clients and contributing to knowledge transfer within the organization.

Requirements

• 10+ years of experience as a data engineer.
• Familiarity with analytical architectures including Data Warehouses, Data Lakes and Data Lakehouses.
• Knowledge of Microsoft relational engines available - both on-premises (MS SQL Server) and on the cloud (Azure SQL, Azure Synapse Analytics Dedicated Pools).
• Knowledge of query and workload optimization.
• Knowledge of administrating and managing analytical solutions both on premises and on the cloud.
• Knowledge of NoSQL offerings on Azure (e.g. CosmosDB).
• Knowledge of setting up Data Lakes on ADLS gen 2 and Azure Synapse Analytics.
• Knowledge of using SSIS and Azure Data Factory to set up ETL jobs.
• Knowledge of setting up OLAP solutions using SSAS.
• Familiarity with Azure Data Catalog to manage data lake metadata.
• Familiarity with Azure HD Insight.
• Familiarity with the Hadoop ecosystems, including tools like Hive, Spark and Kafka.
• Familiarity with Azure Functions to perform lightweight transformations.
• Knowledge of governance over Azure based analytical solutions including using tools such as Purview, Active Directory, Key Vault, Azure DevOps, etc.
• Knowledge of using Azure Stream Analytics to capture and analyze data in real time.
• Knowledge of setting up data warehouse solutions both on-premises (using MS SQL Server) and on the cloud (using Azure Synapse Analytics).
• 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).
• Knowledge of implementing common ETL patterns to support data warehouse workloads.
• Knowledge of using U-SQL, PolyBase and Azure Data Lake Analytics to perform federated querying.
• Knowledge of PowerBI.
• Familiarity with SSRS.
• Databricks Experience: Experience with Snowflake is required.

Nice to Have:

• An MSc in Computer Science or other relevant field.
• Familiarity with DataOps
• Familiarity with Azure Cognitive Services.
• Familiarity with Azure ML.
• Familiarity with MLOps.
• Familiarity of containerization tools and frameworks (Docker, Kubernetes, etc.)

Benefits

• Salary paid in USD
• Six-month career advancing opportunities
• Supportive and friendly work environment
• Premium medical insurance [employee +family]
• English language development courses
• Interest-free loans paid over 2.5 years
• Technical development courses
• Planned overtime program (POP)
• Employment referral program
• Premium location in Maadi
• Social insurance