Data Infrastructure & Engineering

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JD - Data Infrastructure & Engineering

• Design and build scalable data pipelines processing financial transactions, market data, and user behaviour • Develop ETL processes integrating data from CDC, banking partners, fund administrators, and market data providers • Build real-time data systems for portfolio tracking, NAV calculations, and transaction processing • Maintain data quality frameworks ensuring accuracy of financial reporting and regulatory compliance • Optimize database performance for sub-second query response on millions of transactions

Analytics & Insights 

• Analyze user behavior to identify drop-off points, conversion bottlenecks, and engagement patterns • Build dashboards and reporting systems for internal teams and regulatory submissions • Conduct cohort analysis to understand customer lifetime value, retention, and product usage • Develop attribution models to measure marketing channel effectiveness and CAC optimization • Create financial models for portfolio performance analysis and risk assessment

Required

• 2-5 years experience in data science, data engineering, or analytics (fintech/finance experience strongly preferred) • Strong programming skills in Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch) • Proficiency in SQL and experience with relational databases (PostgreSQL, MySQL) • Experience building ETL pipelines and working with large datasets (millions of records) • Strong statistical knowledge and experience with A/B testing, regression analysis, time series • Ability to communicate complex technical concepts to non-technical stakeholders • Self-starter comfortable working in a fast-paced startup environment

Preferred

• Experience with cloud platforms (AWS, Azure, GCP) and big data tools (Spark, Airflow, Kafka) • Knowledge of financial products (mutual funds, pension schemes, market indices) • Familiarity with regulatory requirements in Pakistan's financial sector • Experience with visualization tools (Tableau, Power BI, Looker, or custom dashboards) • Background in behavioral economics or consumer psychology