Data Engineer - BI Infrastructure

Personetics is shaping the Cognitive Banking era, harnessing AI to help banks anticipate customer needs, provide actionable insights, and deliver intelligent financial guidance. Our platform continuously analyzes and leverages real-time transactional data, enabling banks to proactively support customers in managing their finances and reaching their goals. As industry leaders—yes, we really are leaders—we partner with the world’s top financial institutions, empowering over 150 million customers monthly across 35 global markets from offices in New York, London, Singapore, São Paulo, and Tel Aviv.

About the position:

We are looking for a Data Engineer to help design, build, and scale the BI data infrastructure that will power data-driven decision-making across our organization. You will play a critical role in leading, defining and implementing data architecture, governance, and pipeline automation, ensuring high-quality, reliable, and accessible data to support analytics, ML models, and business insights.

This is an exciting opportunity to work in a high-impact role, collaborate with cross-functional teams, and contribute to cutting-edge financial data products that serve both our internal teams and customers.

Responsibilities:

• Data Strategy & Architecture – Design and implement a scalable and efficient BI data infrastructure, ensuring high performance, reliability, and security.
• Data Integration & Pipeline Development – Build and maintain automated data pipelines (ETL/ELT) that integrate internal and external data sources into a unified cloud-based data warehouse.
• Data Quality & Governance – Establish best practices for data governance, lineage, monitoring, and compliance, ensuring accuracy, consistency, and security.
• Collaboration & Cross-Team Impact – Partner with Data Science, BI, Product, and Business teams to deliver high-value insights, supporting analytics, ML models, and reporting.
• Technology Leadership – Work with modern data stack tools such as Python, DBT, Databricks, Spark, Looker, Airflow, Kubernetes, and Azure to build a best-in-class BI ecosystem.
• Data-Driven Culture – Advocate for data-driven decision-making across the company by empowering stakeholders with reliable and self-service data access.

Requirements:

• Experience: 4-5 years of hands-on experience in Data Engineering, Business Intelligence, or a related field, with a proven track record of designing and managing scalable data infrastructure.
• Data Warehousing: Expertise in at least one designing and managing cloud-based data warehouses (e.g., Snowflake, Databricks, BigQuery, Redshift).
• Strong SQL and Python skills.
• Experience with at least BI tool (Looker, Tableau, Power BI).
• Proficiency in ETL/ELT frameworks (Airflow, DBT, etc.).
• Familiarity with big data processing tools (Spark, Databricks).
• Experience with cloud platforms (Azure, AWS, or GCP).
• Ability to work independently in a fast-paced environment.
• Excellent communication skills, with the ability to translate complex data concepts for non-technical stakeholders.
• Strong problem-solving skills and a passion for building scalable, high-impact data solutions.

Nice to have:

• Experience in Fintech, SaaS, or data-driven B2B2C environments.
• Knowledge of data governance principles, compliance, and security best practices.
• Hands-on experience with ML model training pipelines.