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Senior Lead Data Engineer
Integrant, Inc.. Engage clients at multiple levels to elicit requirements, assess analytical challenges, and turn them into technical proposals and solution designs.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in data engineering with a focus on designing and implementing analytical architectures, including Data Warehouses, Data Lakes, and Data Lakehouses. Proficient in SQL, Python, and cloud data platforms, with a strong emphasis on mentoring and coaching teams in modern data methodologies.
Highest-signal resume keywords
Data EngineeringAnalytical ArchitecturesSQL ProgrammingCloud Data PlatformsMentoring Engineers
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data WarehousingData LakesETL/ELT ToolsSQLPythonDimensional ModelingData GovernanceData QualityStreaming PipelinesWorkflow Orchestration
Soft Skills
Excellent CommunicationClient EngagementTechnical Proposal WritingTeam Mentoring
Tools & Technologies
Microsoft SQL ServerOracleTeradataSnowflakeDatabricksAzure Data FactoryAWS GlueInformaticaTalendSSIS
Industry Keywords
DataOpsMLOpsData GovernanceCloud Data PlatformsBig Data Ecosystems
Tech Stack
Tools & technologiesAWSAzureCloudETLInformaticaJavaMS SQL ServerNoSQLOraclePythonScalaSparkSQLSSIS
About the role
Key responsibilities & impact- Engage clients at multiple levels to elicit requirements, assess analytical challenges, and turn them into technical proposals and solution designs.
- Select and customize analytical architectures, including Data Warehouses, Data Lakes, Data Lakehouses, Data Fabrics, and Data Meshes, and technically justify them.
- Design and build agentic and LLM-powered solutions on modern data platforms.
- Lead hands-on implementation of data pipelines, warehouses, and lakes from design through performance tuning and production support.
- Design solutions for data ingestion, storage, processing, transformation, enrichment, and presentation for analytical consumption.
- Build data strategies and coach clients and internal teams in modern architectures and methodologies such as DataOps and MLOps.
- Mentor engineers on the team.
Requirements
What you’ll need- 10-12 years of experience in data engineering, including hands-on delivery at a senior level.
- Bachelor's degree in Computer Science, Computer Engineering or other quantitative field.
- 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.
- Deep understanding of analytical architectures including reporting databases, data warehouses, data lakes, data lakehouses, data fabrics, and data meshes.
- Experience mentoring and guiding data engineers.
- Expert-level SQL and strong programming skills in Python or Scala/Java for data processing.
- Extensive experience with at least one enterprise data platform such as Microsoft SQL Server, Oracle, or Teradata.
- Hands-on experience implementing on-premises and cloud data warehouses.
- Strong dimensional modeling knowledge.
- Hands-on experience with ETL/ELT patterns and tools such as SSIS, Informatica, Talend, Azure Data Factory, AWS Glue, or Spark.
- Hands-on experience with data quality, testing, and observability for data pipelines.
- Experience building semantic layers and OLAP models.
- Hands-on experience with workflow orchestration.
- Experience setting up data lakes and lakehouses on cloud object storage using open table formats.
- Experience optimizing query and workload performance and setting up high availability configurations.
- Experience administering analytical solutions on-premises and in the cloud.
- Experience building streaming pipelines.
- Experience with query federation and data virtualization.
- Knowledge of NoSQL databases.
- Knowledge of BI tools.
- Experience with multiple cloud data platforms, such as Azure, AWS, or Google Cloud.
- Hands-on experience with Snowflake or Databricks.
- Experience estimating, monitoring, and optimizing cloud data platform costs.
- Experience implementing data governance and security.
- Experience with CI/CD and version control for data solutions.
- Hands-on exposure to LLM and agentic solutions in PoC or production.
- Experience with AI-assisted development.
- Familiarity with DataOps.
- Familiarity with Agent Protocols, transformation frameworks, MLOps and ML platforms, cloud AI services, containerization, big data ecosystems, and serverless functions is nice to have.
- Excellent written and spoken English is required.
Benefits
Comp & perks- 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