Data Engineer - BI Infrastructure

Description

Personetics is the global leader in financial data-driven personalization, helping financial institutions deepen client relationships through enhanced financial wellness. We serve 130+ financial institutions and reach 150 million customers across 35 global markets, with 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.