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 ResponsibilitiesRequired 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 Required
- 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 PostgreSQL or MySQL
- Familiarity with Apache Airflow, Azure Data Factory, or similar ETL tools
- Experience with cloud platforms (AWS, Azure, or Google Cloud)
- Knowledge of Python or another programming 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
What We Do
We are a global team who's passionate about transformative enterprise solutions & intelligent design. Our solutions and designs are out to reshape the way people interact with technology. BlackStone eIT supplies innovative solutions to automate and digitally transform human and information intensive processes. We empower breakthrough business results with smarter workflows, augmented business intelligence with AI insights, and through real-time situational awareness which all drive better business outcomes. BlackStone offers a portfolio of next generation solutions, tools, and technologies to be used as a platform to transform traditional organizations into modern smart organizations. Our solutions are designed to dramatically reduce operating costs, increase competitiveness, mitigate risk, boost internal productivity, improve the customer and employee experience, and to make the previously impossible, possible
