ML Feature Engineer

Job ID: 43623

Location: Bangalore, IN

Area of interest: Technology

Job type: Regular Employee

Work style: Office Working

Opening date: 11 Nov 2025

Job Summary

• We are seeking an experienced Senior Data Engineer (8+ years) to drive the design, development, and scaling of enterprise-grade data platforms and AI-ready pipelines. This role requires deep hands-on expertise in distributed data processing, data lakes/lakehouse architectures, real-time streaming, and cloud-native data engineering (Azure/AWS).
• The ideal candidate is highly skilled in Python, Spark, SQL, cloud data services, orchestration frameworks, and modern metadata, quality, and lineage practices. This role will focus on building secure, scalable, and reusable data infrastructure that powers analytical, machine learning, and generative AI workloads.
• You will collaborate closely with data scientists, ML engineers, and product technology teams to build production-grade data products, feature pipelines, and self-service data capabilities across structured, semi-structured, and unstructured data domains.

Key Responsibilities

Strategy

• Shape and execute enterprise data engineering strategy supporting AI/ML adoption at scale.
• Drive design and evolution of lakehouse architecture, data mesh patterns, and scalable compute environments.
• Standardize data ingestion, transformation, feature engineering, and observability practices across teams.
• Evaluate emerging cloud data services, open-table formats (e.g., Delta/Parquet), and metadata platforms to future-proof data foundations.

Business

• Understand complex business data domains, operational systems, and analytics use cases to build aligned data assets.
• Partner with data scientists to create production-grade feature pipelines, model inputs, and real-time inference data flows.
• Work with product, engineering, and analytics teams to deliver AI-driven insights, automation, and decision-support systems.

Processes

• Work with product, engineering, and analytics teams to deliver AI-driven insights, automation, and decision-support systems.
• Architect and maintain data lakes, lakehouses, data marts, and streaming pipelines (Kafka / Kinesis / EventHub).
• Implement automated data quality, lineage, cataloging, and governance frameworks.
• Develop feature stores and reusable data assets for ML/LLM workloads.
• Enable real-time data ingestion, event processing, and low-latency transformations.
• Integrate data with microservices and real-time APIs for ML model serving and monitoring.
• Establish CI/CD automation, modular code practices, and version control for data pipelines.
• Ensuring code quality checks and remediations with SonarQube, Nexus, VPT Scans, etc.
• Good to have knowledge of building containerized applications.
• Optimize cost, performance, and reliability across compute, storage, and orchestration layers.

People & Talent

• Mentor junior and mid-level data engineers to build deep engineering excellence.
• Champion best practices in distributed processing, cloud architecture, and data observability.
• Drive continuous learning in data engineering, ML-ready data design, and emerging AI technologies.
• Collaborate closely with ML engineering teams.

Risk Management

• Implement security-first design for sensitive data handling, encryption, and access control.
• Ensure pipeline reliability, fault tolerance, and incident-ready monitoring.
• Manage risk for data integrity, model drift dependencies, and real-time data service SLAs.

Governance

• Maintain high-quality documentation of data pipelines, ML workflows, and architectural components.
• Ensure all solutions comply with architecture review frameworks (ARF) and data governance standards.
• Participate in regular architectural and code review boards to ensure continuous improvement.

Regulatory & Business Conduct

• Display exemplary conduct and live by the Group's Values and Code of Conduct.
• Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct.
• Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters.

Key stakeholders

• Head of Data Engineering & AI
• Domain Architects and Enterprise Data Architects
• Product Owners & Business Analysts
• Data Scientists and MLOps Engineers
• Cloud Platform Engineering Teams
• Risk & Compliance Partners

Skills and Experience

• Data Engineering & Pipelines
• SQL
• Python
• Spark / PySpark
• Data Science
• Cloud Platforms (Azure / AWS)

Qualifications

• Education: Bachelor's or Master's Degree In Computer Science, Data Engineering, or Related Fields.
• Certifications (Preferred): Azure Or Aws Data Engineering Certification, Databricks, Kafka/Streaming Platforms, Airflow/Orchestration.
• Languages: English

About Standard Chartered

We're an international bank, nimble enough to act, big enough for impact. For more than 170 years, we've worked to make a positive difference for our clients, communities, and each other. We question the status quo, love a challenge and enjoy finding new opportunities to grow and do better than before. If you're looking for a career with purpose and you want to work for a bank making a difference, we want to hear from you. You can count on us to celebrate your unique talents and we can't wait to see the talents you can bring us.

Our purpose, to drive commerce and prosperity through our unique diversity, together with our brand promise, to be here for good are achieved by how we each live our valued behaviours. When you work with us, you'll see how we value difference and advocate inclusion.

Together we:

• Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do
• Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well
• Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term

What we offer

In line with our Fair Pay Charter, we offer a competitive salary and benefits to support your mental, physical, financial and social wellbeing.

• Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations.
• Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum.
• Flexible working options based around home and office locations, with flexible working patterns.
• Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits
• A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning.
• Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.