he Business Data Engineering Lead is responsible for transforming raw data into actionable insights that drive business decisions across company functions (executive leadership, Sales, Marketing, Finance, People, etc). This role involves extracting and integrating data from various sources, building ETL pipelines, calculating key metrics, and developing visualizations to support strategic decision-making. The ideal candidate combines technical expertise with business acumen and strong communication skills to bridge the gap between data and business needs.
Responsibilities:
Collaborate with executives and business teams (sales, marketing, finance, HR, operations) to understand data needs and translate them into analytical solutions.
Extract, clean, and integrate data from various sources, including databases, data warehouses, and external systems.
Design, build, and maintain ETL pipelines to ensure efficient data processing and transformation.
Develop and calculate key performance metrics (KPIs) tailored to business objectives.
Create clear and compelling dashboards and visualizations to communicate insights effectively.
Perform data analysis to identify trends, opportunities, and risks that inform strategic decision-making.
Ensure data accuracy, consistency, and integrity across all reporting and analytics efforts.
Continuously improve data models, workflows, and reporting processes to enhance efficiency and scalability.
Stay up to date with industry trends and emerging technologies in data engineering and business intelligence.
Educate and support business stakeholders in using data-driven insights for better decision-making. Provide analytical insights beyond just providing the data.
Requirements: 5+ years in data engineering, BI, or a related field.
BSc/MSc in Computer Science, Data Science, Engineering, or related.
Strong Python skills for data processing and automation.
Software engineering best practices (Git, code review, testing, CI/CD).
Business acumen with the ability to understand key metrics and drive decisions.
Strong problem-solving and analytical skills for KPI development.
Excellent communicationability to translate complex data into actionable insights (including in English).
Collaborative mindset to align data solutions with business needs.
Adaptability & Learning Agility - learning new tools, technologies, and business domains.
Self-starter with a proactive, ownership-driven approach.
Preferred Qualifications:
SQL proficiency for querying and managing databases.
Experience with ETL, data modeling, and warehousing.
Experience with BI tools (Tableau preferred).
Cloud data platforms.
Familiarity with advanced analytics (ML, predictive modeling).
This position is open to all candidates.