Cloud Data Engineer responsible for modern Data & AI solutions on Microsoft Azure. Collaborating with clients and teams to develop production - ready data platforms and support analytics.
About the role
- Data Engineer responsible for building real-time data pipelines and analytics at Branch. Collaborating on a data platform for high availability and performance handling petabyte-scale data.
Responsibilities
- Architect, build, and own real-time and batch data pipelines that power attribution decisions and marketing insights.
- Deliver high-quality, reliable datasets for customer dashboards, fraud systems, and internal analytics use cases.
- Optimize ingestion and aggregation performance using tools like Flink, Spark, Kafka, and Druid.
- Partner with the Data Platform team to make infrastructure-level decisions that impact performance, latency, and cost.
- Own schema design, versioning, and deployment of datasets across Iceberg, S3, and other analytical data stores.
- Build and maintain robust monitoring, alerting, and self-healing mechanisms to ensure high system availability.
- Collaborate cross-functionally with Product, Customer Success, and Data Science to identify and deliver new data capabilities.
Requirements
- 5+ years of software engineering experience, ideally in data engineering or large-scale backend systems.
- Proficiency in SQL and at least one backend language (Java, or Python).
- Understanding of distributed systems, data modeling, and real-time data processing.
- Hands-on experience with AWS cloud tools and big data platforms such as Kafka, Flink, Spark, Airflow, dbt, Druid.
- A solid grasp of data warehousing principles and familiarity with columnar storage formats (Parquet, Avro).
- Curiosity and drive to work with event-driven data systems that operate at massive scale.
- Strong communication skills and a desire to collaborate across time zones and teams.
Benefits
- Health and wellness programs
- Paid time off
- Retirement planning options
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