Overview
BlackStone eIT is seeking an experienced Senior Data Platform Engineer to lead the design, development, and maintenance of our enterprise data platforms. In this role, you will ensure that our data infrastructure is scalable, reliable, and optimized to support advanced analytics and business intelligence efforts. You will work closely with data engineers, data scientists, and IT teams to develop robust data platforms that facilitate seamless data ingestion, processing, storage, and accessibility. This is an opportunity to make significant contributions to BlackStone eIT’s data strategy and technological advancement. Key Responsibilities Design, build, and maintain scalable data platforms to support diverse data workloads. Develop and optimize ETL/ELT pipelines to ensure efficient data movement and transformation. Collaborate with cross-functional teams to translate business requirements
Full job description
Full Job Description
BlackStone eIT is seeking an experienced Senior Data Platform Engineer to lead the design, development, and maintenance of our enterprise data platforms. In this role, you will ensure that our data infrastructure is scalable, reliable, and optimized to support advanced analytics and business intelligence efforts.
You will work closely with data engineers, data scientists, and IT teams to develop robust data platforms that facilitate seamless data ingestion, processing, storage, and accessibility. This is an opportunity to make significant contributions to BlackStone eIT’s data strategy and technological advancement.
Key Responsibilities
- Design, build, and maintain scalable data platforms to support diverse data workloads.
- Develop and optimize ETL/ELT pipelines to ensure efficient data movement and transformation.
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
- Ensure data platform security, governance, and compliance with relevant regulations.
- Monitor platform performance, troubleshoot issues, and implement improvements.
- Provide technical leadership and mentorship to junior data engineers.
- Stay updated with the latest trends and technologies in data platform engineering.
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- Platform architecture: pipeline design patterns, orchestration strategy, infrastructure-as-code, monitoring stack
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- Enterprise data extraction: SAP FI/CO (budget, actuals, commitments via OData/RFC), Microsoft Graph API (SharePoint, M365), SuccessFactors OData API — you own the extraction approach and build the first pipelines yourself
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- Staging layer design: PostgreSQL staging schema, raw-to-clean transformation patterns, refresh strategies
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- Ingestion observability: logging standards, alerting on failures, monitoring dashboards for pipeline health
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- Data quality framework: defining quality checks, deciding what pauses a pipeline vs. what triggers a warning
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- Classification enforcement: working with the Governance Lead to embed automated classification tagging into every pipeline
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- Technical mentorship: setting standards and reviewing work for the Senior Data Platform Engineer
Requirements
- Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
- 8+ years of experience in data engineering, with a focus on data platform architecture and development.
- Strong proficiency in SQL and experience with relational and NoSQL databases.
- Hands-on experience with cloud data platforms such as AWS, Azure, or Google Cloud.
- Experience with big data technologies like Hadoop, Spark, and data warehousing solutions.
- Knowledge of data governance, security, and compliance standards.
- Excellent problem-solving and communication skills.
- Proven ability to lead technical projects and mentor team members.
- Required Skills & Technologies
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- SAP data extraction: OData services, RFC/BAPI, SAP Data Services, or CDS views — hands-on experience pulling data from SAP FI/CO modules
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- Python — async data pipelines, background jobs, scheduled tasks
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- PostgreSQL — schema design, migrations (Alembic), query optimization, partitioning
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- Azure Data Lake Storage + Synapse Analytics
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- Microsoft Graph API — SharePoint, M365, organizational data
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- Apache Airflow or Azure Data Factory
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- dbt or equivalent for transformation and quality testing
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- Redis — queue management, TTL, cache invalidation
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- Observability — structured logging, Azure Monitor or Prometheus/Grafana
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- Docker — containerized pipeline jobs
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- Infrastructure-as-code (Terraform or equivalent)
Benefits
- Paid Time Off
- Performance Bonus
- Training & Development
Qualifications And Requirements
Mid-Senior level
Requirements & qualifications
Mid-Senior level
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