We are seeking a hands-on Senior Data Engineer to lead the development, support, and continuous improvement of our Azure-based data platform. This role combines data engineering, platform operations, and technical leadership, ensuring reliable, scalable, and high-performing data solutions across the enterprise.
Key Responsibilities
- Design, build, and support scalable data pipelines using Azure Databricks, PySpark, Python, and SQL.
- Develop and maintain data ingestion, transformation, and orchestration solutions across the Azure data ecosystem.
- Provide production support, incident resolution, root cause analysis, and platform monitoring.
- Implement integrations with Braze and other downstream data consumers.
- Drive platform reliability through automation, observability, CI/CD, and operational best practices.
- Partner with architects, product teams, and stakeholders to deliver data platform enhancements.
- Lead technical delivery, code reviews, and engineering standards while coordinating offshore development teams.
- Contribute to cloud infrastructure, Infrastructure-as-Code, and platform optimization initiatives.
Required Skills & Experience
- 6+ years of experience in Data Engineering and Data Platform delivery.
- Strong expertise in:
- Azure Databricks
- PySpark / Apache Spark
- Python
- SQL
- Azure Data Lake Storage (ADLS Gen2)
- Azure Data Factory (ADF)
- Azure DevOps and CI/CD
- Experience supporting enterprise-scale data platforms in production environments.
- Strong troubleshooting, performance tuning, and operational support skills.
- Experience leading technical delivery and collaborating with offshore teams.
- Excellent communication and stakeholder management skills.
Preferred Qualifications
- Terraform or Bicep (Infrastructure as Code).
- Azure platform engineering and cloud infrastructure experience.
- Monitoring and observability tools (Azure Monitor, Log Analytics, Splunk, Dynatrace, etc.).
- Production release management and platform operations experience.
- Experience with Braze, Martech, or Customer Data Platforms (CDP).
Nice to Have
- Event-driven and streaming architectures.
- Azure Event Hubs, Kafka, or similar technologies.
- Data quality, governance, and observability frameworks.
- Customer engagement, marketing activation, or financial services domain experience.
