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

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