Data Platform Engineer
BlackStone eIT is looking for a skilled Data Platform Engineer to join our dynamic team. You will be responsible for designing, building, and maintaining scalable data platforms that support the company’s data processing and analytics needs.
In this role, you will collaborate with data engineers, analysts, and other stakeholders to develop efficient data pipelines, ensure data quality, and contribute to the overall data infrastructure architecture. This is a fantastic opportunity to advance your career by working with cutting-edge technologies and helping shape BlackStone eIT’s data capabilities.
Key Responsibilities
Required Skills & Technologies
- Python — async data pipelines, background jobs, scripting
- PostgreSQL — schema design, migrations (Alembic), query optimization
- Azure Data Lake Storage + Synapse Analytics
- dbt — transformation, testing, documentation
- Apache Airflow or Azure Data Factory
- Data quality frameworks (Great Expectations, dbt tests, or custom)
- Observability — structured logging, alerting, Azure Monitor or Prometheus/Grafana
- Microsoft Graph API — SharePoint, M365 data extraction
- Redis — queue management, caching
- Docker — containerized pipeline jobs
- SQL — advanced analytical queries, window functions, performance tuning
- Develop and maintain data pipelines for ingestion, processing, and storage of large datasets
- Implement ETL/ELT processes to transform raw data into usable formats
- Collaborate with cross-functional teams to understand data requirements and deliver solutions
- Ensure data quality, consistency, and reliability across platforms
- Optimize database performance and monitor platform health
- Assist in the design and implementation of data governance and security measures
- Document data infrastructure and processes for operational clarity
Requirements
- Bachelor’s degree in Computer Science, Information Technology, or a related field
- 3+ years of experience in data engineering or data platform development
- Proficiency in SQL and experience with relational databases like PostgreSQL or MySQL
- Familiarity with data pipeline and ETL tools such as Apache Airflow, Azure Data Factory, or similar
- Experience with cloud platforms (AWS, Azure, or Google Cloud)
- Knowledge of Python or another programming/scripting language for data processing
- Understanding of data security, governance, and quality best practices
- Strong analytical and problem-solving skills
- Good communication skills and ability to work effectively in a team environment
Benefits
- Paid Time Off
- Performance Bonus
- Training & Development
Skills
As published by workable · 8 questions · 8 written answers
First name, Last name, Email, Phone, Education, Experience, Summary, Resume, Cover letter
- How Many years of experince as a Data Platform Engineer ?
- How Many years of experince as a - Data warehouse build: ADLS + Synapse/Fabric — dimensional models, ingestion patterns, governed access views - Data quality monitoring: automated checks on completeness, freshness, row counts, and classification coverage — quality failures pause pipelines, not skip records - Additional source ingestion: pipelines for data sources beyond the initial three (research center data, PMO data, procurement systems)
- How Many years of experince as a - Data mesh enablement: governed data products that entities own and the platform makes accessible - Agentic platform data readiness: clean, structured data outputs formatted to the contracts defined by the Principal AI Engineer - Schema deployment: migration scripts, versioning, blue-green deployment support - Pipeline maintenance: monitoring, troubleshooting, and optimizing existing pipelines
- Are you Arabic Speaker ?
- Are you located in UAE ?
- what is your nationality ?
- Are you ready to start immediately ?
- please mention your current salary and your expected salary ?