Engineering Manager Data

Job description

About us
slice
A new bank for a new India
slice’s purpose is to make the world better at using money and time, with a major focus on building the best consumer experience for your money.

We’ve all felt how slow, confusing, and complicated banking can be.

So, we’re reimagining it.

We’re building every product from scratch to be fast, transparent, and feel good, because we believe that the best products transcend demographics, like how great music touches most of us.
Our cornerstone products and services: slice savings account, slice UPI credit card, slice UPI, and slice business are designed to be simple, rewarding, and completely in your control.

At slice, you’ll get to build things you’d use yourself and shape the future of banking in India.

We tailor our working experience with the belief that the present moment is the only real thing in life.

And we have harmony in the present the most when we feel happy and successful together.
We’re backed by some of the world’s leading investors, including Tiger Global, Insight Partners, Advent International, Blume Ventures, and Gunosy Capital.
About the role
We’re looking for Engineering Manager to lead our Data Platform and MLOps teams at slice.

In this role, you’ll be responsible for building and scaling a high-performing team that powers data infrastructure, real-time streaming, ML enablement, and data accessibility across the company.

You'll partner closely with ML, product, platform, and analytics stakeholders to build robust systems that deliver high-quality, reliable data at scale.

You will drive AI initiatives to centrally build AP platform and apps which can be leveraged by various functions like legal, CX, product in a secured manner.
This is a hands-on leadership role perfect for someone who enjoys solving deep technical problems while growing people and teams.
What you will do
- Lead and grow the data platform pod focused on all aspects of data (batch + real-time processing, ML platform, AI tooling, Business reporting, Data products – enabling product experience through data)
- Maintain hands-on technical leadership - lead by example through code reviews, architecture decisions, and direct technical contribution
- Partner closely with product and business stakeholders to identify data-driven opportunities and translate business requirements into scalable data solutions
- Own the technical roadmap for our data platform including infra modernization, performance, scalability, and cost efficiency
- Drive the development of internal data products like self-serve data access, centralized query layers, and feature stores
- Build and scale ML infrastructure with MLOps best practices including automated pipelines, model monitoring, and real-time inference systems
- Lead AI platform development for hosting LLMs, building secure AI applications, and enabling self-service AI capabilities across the organization
- Implement enterprise AI governance including model security, access controls, and compliance frameworks for internal AI applications
- Collaborate with engineering leaders across backend, ML, and security to align on long-term data architecture
- Establish and enforce best practices around data governance, access controls, and data quality
- Ensure regulatory compliance with GDPR, PCI-DSS, SOX through automated compliance monitoring and secure data pipelines
- Implement real-time data processing for fraud detection and risk management with end-to-end encryption and audit trails
- Coach engineers and team leads through regular 1:1s, feedback, and performance conversations
What you will need
- 9+ years of engineering experience, including 2+ years managing data or infra teams with proven hands-on technical leadership
- Strong stakeholder management skills with experience translating business requirements into data solutions and identifying product enhancement opportunities
- Strong technical background in data platforms, cloud infrastructure (preferably AWS), and distributed systems
- Experience with tools like Apache Spark, Flink, EMR, Airflow, Trino/Presto, Kafka, and Kubeflow/Ray plus modern stack: dbt, Databricks, Snowflake, Terraform
- Hands on experience building AI/ML platforms including MLOps tools and experience with LLM hosting, model serving, and secure AI application development
- Proven experience improving performance, cost, and observability in large-scale data systems
- Expert-level cloud platform knowledge with container orchestration (Kubernetes, Docker) and Infrastructure-as-Code
- Experience with real-time streaming architectures (Kafka, Redpanda, Kinesis)
- Understanding of AI/ML frameworks (TensorFlow, PyTorch), LLM hosting platforms, and secure AI application development patterns
- Comfort working in fast-paced, product-led environments with ability to balance innovation and regulatory constraints
- Bonus: Experience with data security and compliance (PII/PCI handling), LLM infrastructure, and fintech regulations
Life at slice
Life so good, you’d think we’re kidding:
- Competitive salaries.

Period.
- An extensive medical insurance that looks out for our employees & their dependents.

We’ll love you and take care of you, our promise.
- Flexible working hours.

Just don’t call us at 3AM, we like our sleep schedule.
- Tailored vacation & leave policies so that you enjoy every important moment in your life.
- A reward system that celebrates hard work and milestones throughout the year.

Expect a gift coming your way anytime you kill it here.
- Learning and upskilling opportunities.

Seriously, not kidding.
- Good food, games, and a cool office to make you feel like home.

An environment so good, you’ll forget the term “colleagues can’t be your friends”.

Required Skill Profession

Operations Specialties Managers