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Open nowPosted 69 days ago

Senior Lead Data Engineer - Databricks

Workable (global search)108,016 open roles

Where
Maadi, Al Qāhirah, Egypt
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Your applicationOpen nowSenior Lead Data Engineer - DatabricksWorkable (global search) · Maadi, Al Qāhirah, Egypt

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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 69 days ago

Workable (global search) median: 7 days open

The posting

Description

We're on the lookout for exceptional individuals to join our team as Senior Lead Data Engineers – Databricks. As part of our team, you'll play a key role in designing and delivering modern, scalable data platforms for clients across multiple industries, leveraging Azure and Databricks technologies.

You will lead the design, development, and optimization of end-to-end data engineering solutions built on modern Lakehouse architectures. Working closely with clients and cross-functional teams, you'll translate business requirements into scalable, high-performance data platforms while mentoring engineers and driving technical excellence.

Requirements

  • Responsibilities
  • Lead the design, development, and maintenance of scalable data engineering solutions using Azure and Databricks.
  • Design and implement modern Lakehouse architectures following industry best practices.
  • Build and optimize large-scale batch and streaming data pipelines.
  • Develop ETL/ELT pipelines using Databricks, PySpark, SQL, and Azure Data Factory.
  • Design, implement, and optimize Delta Lake solutions for reliable and performant data processing.
  • Collaborate with clients to gather requirements and translate business needs into technical solutions.
  • Optimize Spark workloads for performance, scalability, and cost efficiency.
  • Design and maintain enterprise-grade Data Warehouses, Data Lakes, and Lakehouses.
  • Implement data governance, security, and metadata management using Azure services such as Purview, Key Vault, and Microsoft Entra ID (Azure Active Directory).
  • Establish CI/CD pipelines and DevOps practices for data engineering workloads.
  • Mentor and coach junior data engineers while promoting engineering best practices.
  • Participate in architecture discussions, solution design, and technical leadership initiatives.
  • Contribute to internal knowledge sharing and continuous improvement.
  • Requirements
  • Required
  • 10+ years of professional experience in Data Engineering.
  • 4+ years of hands-on experience with Databricks.
  • Strong experience developing data pipelines using PySpark and Apache Spark.
  • Strong experience designing and implementing Lakehouse architectures.
  • Experience working with Delta Lake and Medallion Architecture.
  • Strong knowledge of SQL and Python.
  • Experience with Azure Data Factory.
  • Experience working with Azure Data Lake Storage Gen2 (ADLS Gen2).
  • Experience with Azure Synapse Analytics.
  • Experience with Data Warehousing concepts and dimensional modeling.
  • Strong understanding of ETL and ELT design patterns.
  • Experience optimizing Spark jobs, partitioning strategies, joins, caching, and workload performance.
  • Experience with Git and Azure DevOps CI/CD pipelines.
  • Experience implementing secure data platforms using Azure Key Vault, Microsoft Entra ID, and Microsoft Purview.
  • Experience building scalable enterprise data platforms in Azure.
  • Experience working directly with clients and gathering technical requirements.
  • Experience mentoring engineers and leading technical initiatives.
  • Strongly Preferred
  • Experience with Snowflake.
  • Experience building real-time streaming solutions using Structured Streaming, Kafka, or Event Hubs.
  • Experience with Databricks Workflows.
  • Experience with Delta Live Tables.
  • Experience with Unity Catalog.
  • Experience with Databricks SQL.
  • Experience with MLflow.
  • Experience with dbt.
  • Experience with Airflow or other orchestration platforms.
  • Experience working in Agile environments.
  • Nice to Have
  • MSc in Computer Science or a related field.
  • Experience with DataOps practices.
  • Experience with MLOps.
  • Experience with Azure Machine Learning.
  • Experience with Azure Cognitive Services.
  • Experience with Docker and Kubernetes.
  • Experience working with Microsoft Fabric.
  • Experience with Power BI.
  • Technical Skills
  • Core Technologies
  • Azure Databricks
  • Apache Spark
  • PySpark
  • SQL
  • Python
  • Delta Lake
  • Azure Data Factory
  • Azure Synapse Analytics
  • ADLS Gen2
  • Snowflake
  • Data Engineering
  • Data Warehousing
  • Data Lakes
  • Lakehouse Architecture
  • Medallion Architecture
  • Dimensional Modeling
  • ETL / ELT
  • Batch Processing
  • Streaming Data Pipelines
  • Data Governance
  • Performance Optimization
  • Azure Ecosystem
  • Azure DevOps
  • Microsoft Purview
  • Azure Key Vault
  • Microsoft Entra ID
  • Azure Functions
  • Event Hubs
  • Nice-to-Have Technologies
  • Kafka
  • Airflow
  • dbt
  • MLflow
  • Docker
  • Kubernetes
  • Power BI

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
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