Senior Lead Data Engineer

Integrant is looking for game changers to join our team as a Senior Lead Data Engineer. This is a senior hands-on leader who designs data and AI solutions end to end and builds them. Youll be responsible for designing solutions for the ingestion storage processing transformation enrichment and presentation of data for analytical consumption and for personally implementing the critical parts of those solutions.

• Engage clients at multiple levels to elicit requirements assess their current analytical challenges and turn them into technical proposals and solution designs.
• Select and customize analytical architectures (Data Warehouses Data Lakes Data Lakehouses Data Fabrics Data Meshes etc.) and technically justify how they meet each clients needs.
• Design and build agentic and LLM-powered solutions on top of modern data platforms.
• Lead hands-on implementation of data pipelines warehouses and lakes from design through performance tuning and production support.
• Build data strategies and coach clients and internal teams in the latest architectures and methodologies (DataOps MLOps etc.) including mentoring engineers on the team.

Architecture & Leadership

• 10-12 years of experience in data engineering including hands-on delivery at a senior level.
• Bachelors degree in Computer Science Computer Engineering or other quantitative field. Post Graduate degrees preferable.
• The ability to interact with stakeholders at multiple levels within a given organization understand current analytical challenges and gather requirements.
• Excellent written and spoken English with the ability to present solutions to technical and business audiences.
• Proven experience writing technical proposals and solution designs for clients.
• A deep understanding of the evolution of analytical architectures from reporting databases to data warehouses data lakes data lakehouses data fabrics data meshes and beyond with the ability to technically justify how a proposed architecture meets a clients analytical needs.
• Experience mentoring and guiding data engineers.

Hands-on Data Engineering

• Expert-level SQL and strong programming skills in Python (or Scala/Java) for data processing.
• Extensive experience with at least one enterprise data platform (e.g. Microsoft SQL Server stack Oracle Teradata).
• Hands-on experience implementing data warehouses both on-premises and in the cloud (e.g. SQL Server Oracle Azure Synapse/Fabric Amazon Redshift Google BigQuery).
• Strong dimensional modeling: Dimensions Facts Slowly Changing Dimensions Outriggers Role-Playing Junk Degenerate and Multi-valued Dimensions; Transactional Periodic Snapshot and Accumulating Snapshot Facts.
• Hands-on experience implementing common ETL/ELT patterns using tools such as SSIS Informatica Talend Azure Data Factory AWS Glue or code-based frameworks (e.g. Spark).
• Hands-on experience implementing data quality testing and observability for data pipelines (e.g. dbt tests Great Expectations Monte Carlo Soda).
• Experience building semantic layers and OLAP models (e.g. SSAS Power BI semantic models LookML dbt semantic layer).
• Hands-on experience with workflow orchestration (e.g. Apache Airflow Azure Data Factory AWS Step Functions Databricks Workflows).
• Experience setting up data lakes and lakehouses on cloud object storage (e.g. ADLS Gen2 Amazon S3 Google Cloud Storage) using open table formats (e.g. Delta Lake Apache Iceberg Apache Hudi).
• Experience optimizing query and workload performance and setting up high availability configurations.
• Experience administering and managing analytical solutions both on-premises and in the cloud.
• Experience building streaming pipelines (e.g. Kafka Kinesis Event Hubs Google Pub/Sub Spark Structured Streaming).
• Experience with query federation and data virtualization (e.g. Trino/Starburst Amazon Athena PolyBase BigQuery federated queries).
• Knowledge of NoSQL databases (e.g. MongoDB Cosmos DB DynamoDB Cassandra).
• Knowledge of BI tools (e.g. Power BI Tableau Looker Qlik).

Cloud Platforms & Governance

• Experience with multiple cloud data platforms (e.g. Microsoft Azure AWS Google Cloud).
• Hands-on experience with Snowflake or Databricks.
• Experience estimating monitoring and optimizing cloud data platform costs (e.g. warehouse sizing compute/storage trade-offs Snowflake credits Databricks DBUs) and reflecting them in client proposals.
• Experience implementing data governance and security: cataloging lineage access control and secrets management (e.g. Unity Catalog Microsoft Purview AWS Lake Formation Collibra cloud IAM HashiCorp Vault).
• Experience with CI/CD and version control for data solutions (e.g. GitHub Actions GitLab CI Azure DevOps).

AI & Agentic

• Hands-on exposure to LLM and agentic solutions in PoC or production (e.g. LangGraph/AutoGen/CrewAI/LlamaIndex/n8n).
• Experience with AI-assisted development (e.g. Cursor/Codex/Claude Code).
• Familiarity with DataOps.

Nice to Have

• Familiarity with Agent Protocols (e.g. MCP).
• Familiarity with transformation frameworks (e.g. dbt).
• Familiarity with MLOps and ML platforms (e.g. MLflow Azure ML Amazon SageMaker Vertex AI).
• Familiarity with cloud AI services (e.g. Azure AI services Amazon Bedrock Vertex AI).
• Familiarity with containerization tools and frameworks (Docker Kubernetes etc.).
• Familiarity with the big data ecosystem including Spark and Hive (e.g. on Databricks Amazon EMR Dataproc HDInsight).
• Familiarity with serverless functions for lightweight transformations (e.g. AWS Lambda Azure Functions Google Cloud Functions).

• Salary paid in USD
• Career progression reviews every six months
• Supportive and friendly work environment
• Premium medical insurance employee family
• Social insurance
• English language development courses
• Interest-free loans paid over 2.5 years
• Technical development courses
• Employment referral program
• Premium location in Maadi

Required Experience:

Senior IC