Jr Data Engineer

About the Role

The Professional Data Engineer at Algoleap designs, builds, and maintains moderately complex data systems to enable analysis and reporting. With limited supervision, you will collaborate on efficiently processing large datasets for decision-making.

Essential Functions:

• Data & Analytical Solutions: Develop scalable, sustainable, and robust data products using advanced engineering and cloud technologies.
• Data Pipelines: Maintain streaming and batch pipelines for seamless ingestion from various sources into lakes or warehouses.
• Data Systems: Review architectures to implement improvements and optimization.
• Data Infrastructure: Prepare infrastructure for efficient storage and retrieval of data.
• Data Formats: Implement formats that improve usability across the organization.
• Stakeholder Management: Partner with multi-functional teams to ensure solutions meet functional needs.
• Data Frameworks: Build prototypes and implement frameworks for advanced analytics initiatives.
• Automated Deployment Pipelines: Implement CI/CD pipelines with appropriate governance.
• Data Modeling: Perform complex modeling aligned with datastore technology for sustainable performance.

Preferred Qualifications

• Cloud Environments: Familiarity with AWS, GCP, or Azure.
• Data Architecture: Experience with data lakes, lakehouses, hubs, ingestion, and governance.
• Data Ingestion: Proficiency in Kafka, AWS Glue, Iceberg, Parquet.
• Data Streaming: Knowledge of Kafka, Flink architectures.
• Data Modeling & Transformation: Strong SQL background with dbt, Airflow, Spark (streaming/tuning), and concepts like SCD.
• Programming: Proficient in Python/Java/Scala with expert-level SQL skills.
• DevOps: Experience in code management, CI/CD, and deployment strategies.
• Data Governance: Understanding of quality, privacy, and security principles.

Experience

We are looking for candidates with a minimum of 2 years of relevant experience (typically 3+ years).