Full Time: Azure Data Engineer

• API Connector Development: Build, maintain, and document scalable API integrations with internal and external platforms to automate data ingestion and synchronization.
• Event-Driven Architecture: Design and implement data pipelines using event-driven frameworks and messaging systems (e.g., Kafka, Kinesis) to support real-time analytics and operational use cases.
• Data Lakehouse Engineering: Manage data ingestion and transformation pipelines feeding into an event house or lakehouse architecture, ensuring consistency and scalability across datasets.
• Data Transformation & Orchestration: Use ETL/ELT tools and scripting to clean, transform, and enrich data from various sources into usable formats for analysts and stakeholders.
• Data Quality & Validation: Establish automated validation rules, monitor data integrity, and proactively resolve quality issues to ensure trust in data systems.
• Collaboration & Enablement: Partner with analytics, business, and engineering teams to understand data requirements and deliver scalable solutions that meet evolving needs.

REQUIREMENTS:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience.
• 3-6 years of experience as a data engineer or in a similar backend data role.
• Experience building and maintaining API integrations and event-driven data pipelines.
• Proficiency in SQL and data pipeline scripting (e.g., Python, PySpark).
• Experience with cloud platforms such as AWS, Azure, or Google Cloud (e.g., S3, Redshift, Snowflake, or Databricks).
• Familiarity with event streaming platforms such as Apache Kafka, Kinesis, or similar.
• Strong attention to detail with a commitment to data accuracy and quality assurance.
• Ability to thrive in a fast-paced, collaborative environment.