Data Infrastructure & Engineering

Mahaana (YC W22); Karachi Division; On-site; PKR 1,500,000 - 2,800,000; Full time

Job summary

Mahaana (YC W22) in Karachi, Pakistan, is seeking a Data Infrastructure & Engineering specialist to design and build scalable data pipelines and real-time systems for financial data. You will handle ETL with CDC feeds, banking partners, fund administrators, and market data providers, ensuring data quality and regulatory compliance.

You will need strong Python and SQL skills, experience with large datasets, and the ability to explain complex concepts to non-technical stakeholders in a fast-paced

Qualifications

• 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

Responsibilities

• 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
• 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

Skills

Python

SQL

ETL pipelines

Statistics

Communication

Startup mindset

Tools

PostgreSQL

MySQL

Spark

Airflow

Kafka

Job description

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