Senior Techno-Functional Python Data & AI Engineering Consultant

Senior Techno-Functional Data & AI Engineering Consultant

Securities Trading Analytics | Python, Kafka, Spark

ROLE PURPOSE

Join us to turn securities-trading data and AI concepts into stable, scalable enterprise solutions. This is a consulting role for a strong Python engineer who can understand trading workflows, shape requirements with business and data stakeholders, and industrialise analytics or AI use cases for production.

BUSINESS OUTCOMES

• Convert trading and execution data into dependable analytics and near-real-time decision support.
• Industrialise proofs of concept into secure, resilient and supportable enterprise applications.
• Create reusable data and AI engineering patterns for securities-trading use cases.

WHAT YOU WILL DO

• Engage business users, product owners, data scientists and architects to define use cases, data needs, controls and measurable outcomes.
• Design and develop Python, Kafka and big-data applications for trading analytics and AI-enabled insights.
• Engineer experimental models and prototypes into tested, deployable and operationally resilient software.
• Analyse data lineage, quality, mappings and business rules across order, trade, instrument and execution datasets.
• Design for non-functional requirements including stability, capacity, scalability, performance, security and manageability.
• Support cloud and platform decisions by assessing technical, economic and risk considerations.
• Own code quality, automated tests, release readiness, observability and production-issue resolution.
• Apply AI-assisted development techniques with appropriate review, validation and documentation.

DOMAIN CAPABILITIES (DESIRABLE)

• Working awareness of securities-trading workflows, with emphasis on listed securities.
• Basic understanding of order, execution, trade and instrument data and how these datasets support analytics and control use cases.
• Ability to translate trading questions into data products, rules, features, metrics and testable acceptance criteria.
• Awareness of front-to-back dependencies and data-quality risks in regulated trading environments.

ENGINEERING CAPABILITIES

• Expert-level Python development and practical use of pandas and NumPy.
• Big-data engineering using technologies such as Spark, Parquet and Hive; familiarity with distributed processing concepts.
• Kafka or comparable messaging middleware and event-driven solution patterns.
• Oracle or PostgreSQL, relational modelling and advanced SQL.
• Unix/Linux, shell scripting, Git/GitLab and build or dependency-management tooling.
• API and integration engineering, automated testing, CI/CD and production support.
• Experience deploying analytics or AI workloads to enterprise infrastructure or cloud platforms.

CONSULTING AND CLIENT ENGAGEMENT

• Facilitate use-case discovery and convert business problems into an executable engineering backlog.
• Explain data, architecture and AI trade-offs to technical and non-technical stakeholders.
• Produce consulting deliverables such as data-flow views, source-to-target mappings, control definitions, solution options and implementation roadmaps.
• Bridge data scientists, platform engineers and trading stakeholders to avoid the gap between prototype and production.
• Contribute accelerators, reusable components and delivery playbooks.

REQUIRED EXPERIENCE

• 8+ years of professional Python engineering experience with demonstrable production code ownership.
• Experience in data-intensive enterprise applications, preferably in capital markets, securities trading or transaction processing (domain exposure is an advantage, not a prerequisite).
• Hands-on experience with Kafka, big-data technologies, relational databases and Linux-based platforms.
• Ability to combine business analysis, data analysis, solution design and software engineering.
• Experience resolving complex production issues across distributed teams.
• Hands-on experience in AI-based development, including delivery using AI coding assistants and AI-enabled engineering practices.
• Excellent written and verbal communication skills (essential).
• Location: Pune preferred.

PREFERRED EXPERIENCE

• Java development capability.
• Cloud-native engineering and container platforms.
• MLOps, model monitoring, retrieval-augmented generation or agentic AI patterns applied in controlled enterprise environments.
• Experience with real-time trading analytics, execution data or market-data integration.