Data Engineer

About CodeNinja

CodeNinja is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations—combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.

Role Overview

We are seeking a skilled Data Engineer with 3+ years of experience to design and build robust, scalable data pipelines supporting financial machine learning forecasting models.

You will be responsible for ingesting, cleaning, validating, and structuring complex multi-source financial datasets to enable high-quality time-series model training and analytics.

This role requires strong technical expertise in ETL/ELT pipelines, financial data processing, and data quality assurance within secure corporate environments.

Key Responsibilities

• Design, develop, and maintain automated ETL/ELT pipelines from CSV/Excel exports within secure enterprise environments.
• Perform data cleaning, normalization, validation, and integrity checks on financial transaction datasets.
• Execute entity mapping, currency standardization, and data synthesis across multiple legal entities and G/L accounts.
• Build exploratory data analysis (EDA) pipelines, including statistical analysis of financial flow patterns and seasonality.
• Develop feature stores with pre-computed lag and rolling statistics for ML forecasting consumption.
• Ensure high data quality through validation frameworks and automated integrity checks.
• Document data pipelines, quality reports, and technical handoff materials for ML Engineering teams.
• Collaborate closely with ML engineers, domain subject matter experts, and stakeholders.

Requirements:
• 3+ years of hands-on experience building production-grade data engineering pipelines.
• Strong Python expertise (Pandas, NumPy) and SQL proficiency.
• Experience using Jupyter notebooks for EDA and reporting.
• Proven experience handling complex financial datasets (transactions, general ledger, settlements, multi-currency data).
• Strong knowledge of data validation frameworks and quality assurance methodologies.
• Experience parsing and processing large CSV/Excel datasets at scale.
• Familiarity with corporate network security protocols and access control environments.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.

Nice to Have

• Financial domain experience (intercompany transactions, treasury operations).
• Experience preparing time-series datasets for ML forecasting models.
• Exposure to orchestration tools such as Airflow, Luigi, or Prefect.
• Experience working with cloud data platforms (AWS S3, GCP BigQuery, Azure Data Lake).

Why Join CodeNinja?

• Work on cutting-edge AI and financial forecasting solutions.
• Collaborate with high-performing engineers and AI specialists.
• Exposure to enterprise-grade secure environments and global clients.
• Opportunity to contribute to impactful, data-driven transformation initiatives.
• A culture that values ownership, growth, and continuous learning.
• Competitive compensation and career progression opportunities.

Equal Opportunity & Disclaimer

CodeNinja is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All employment decisions are made based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, gender, national origin, disability status, or any other characteristic protected by applicable laws.

Only shortlisted candidates will be contacted. CodeNinja reserves the right to modify the job description based on business requirements.

Benefits:
• Provident Fund
• Gym Membership
• Leaves as per the company policy
• Company-paid trips
• Easy Loan Facility for Employees
• Yearly increment
• Maternity Benefits (Leaves & WFH)
• Health Insurance (Maternity covered) – includes spouse and parents (till age 80)