Data Engineer

About the role

Personetics is looking for an experienced Data Engineer to design, build, and scale its Business Intelligence platform. You will work within the R&D team, turning raw transactional data into actionable insights that power both internal dashboards and product‑driven analytics.

Key responsibilities

• Own the design and implementation of a scalable, high‑performance BI data infrastructure.
• Architect end‑to‑end data products, from ingestion through transformation, modeling, storage, and access.
• Build and maintain batch and real‑time ETL/ELT pipelines to support analytics, reporting, and product integrations.
• Establish best practices for data quality, lineage, observability, and governance.
• Integrate modern tools such as Apache Airflow, Databricks, Power BI, and streaming platforms.
• Collaborate with product, engineering, and analytics teams to translate business needs into data solutions.
• Promote a data‑driven culture by enabling self‑service data access for stakeholders.

Required profile

• 5+ years of hands‑on data engineering experience building analytics and BI data products.
• Strong background in both batch and streaming processing.
• Proficiency in Python and SQL.
• Experience with cloud data environments (AWS, Azure, or GCP).
• Degree in Computer Science or a related field.

Required skills

• Apache Airflow (ETL orchestration)
• Databricks or similar lake‑house platforms
• Kafka and Spark Streaming (real‑time processing)
• Python programming
• SQL querying
• Cloud platforms: AWS, Azure, GCP
• Data visualization tools: Power BI, Looker