Lead Data Engineer Mumbai

Liberis Limited; Mumbai; On-site; INR 1,800,000 - 2,500,000; Full time

Job summary

Liberis Limited is seeking an experienced Data Engineer for its Mumbai office to drive innovation in their data platforms and AI capabilities. The role requires collaboration within a dynamic team to design, build, and maintain data pipelines, ensuring data quality and operational health.

Applicants should have at least 8 years of experience, with hands-on experience in building cloud-based data solutions. A strong command of Python and SQL is essential. The position supports career development and offers a hybrid working environment, promoting flexibility while being in the office.

Qualifications

• 8+ years of professional software engineering experience, with at least 4–5 years in data engineering.
• Hands-on experience with Modern Data Stack architectures.
• Strong Python programming skills with clean, maintainable code.

Responsibilities

• Design, build, and maintain data pipelines from Azure SQL to BigQuery.
• Collaborate with analytics engineers for schema validation and data quality.
• Mentor junior engineers and support their career development.

Skills

Software Engineering

Data Engineering

Python Programming

SQL

Cloud Data Platforms

Infrastructure as Code

Data Pipeline Building

Tools

BigQuery

Airflow

DBT

Fivetran

Terraform

Job description

About Liberis

Liberis is building an embedded finance platform that lets partners worldwide offer innovative funding products to small business customers. We are a growth‑stage fintech with teams in London, Nottingham, Atlanta, Stockholm, Munich and Mumbai, and building a global Product, Data & Engineering team that thrives on autonomy, ownership, and impact. Our teams solve real‑world problems for small businesses, shaping products that unlock opportunity at scale.

Engineering – AI‑first Transformation

Engineering is going through an AI‑first transformation, rethinking team structure and shipping practices. We empower teams to make decisions, move fast and take full responsibility for the solutions they deliver. You’ll join a team where curiosity is encouraged and collaboration across Product, Data, Delivery and Engineering is the norm.

Data & Insights Team

We build data platforms and analytics that enable every decision at Liberis to be data‑informed—powering AI and ML capabilities across the company. We focus on reliable, low‑latency pipelines, analytics dashboards, and model serving infrastructure.

Team Composition

Data Platform Engineering: Building and scaling ELT pipelines, managing data infrastructure on GCP, and creating the foundation for analytics and ML feature stores.

Analytics Engineering: Transform raw data into trusted models using DBT and SQL, supporting self‑serve analytics for stakeholders.

Data & Business Intelligence: Build dashboards, partner‑facing reports, and insights that drive decisions and revenue.

Role Responsibilities

• Design, build, and maintain resilient data pipelines ingesting data from Azure SQL, SaaS platforms, and event streams into BigQuery.
• Build and operate ML feature pipelines—low‑latency, real‑time data streams that feed ML models with accurate, fresh features.
• Own operational health of systems: monitoring, alerting, error handling and incident response.
• Collaborate with analytics engineers to validate schema design and establish data quality standards.
• Partner with the AI/ML platform team to design feature stores, streaming feature infrastructure, and model‑serving pipelines.
• Identify and execute optimisation work to improve performance, reliability, and developer velocity.
• Mentor junior engineers, supporting their career development.
• Contribute to technical decisions about platform direction, infrastructure choices and architecture trade‑offs.
• Work cross‑functionally with product teams, analytics engineers, BI specialists and ML platform team to shape data requirements and platform capabilities.

Required Experience & Skills

• 8+ years of professional software engineering experience, with at least 4–5 years in data engineering roles at scale.
• Hands‑on experience building Modern Data Stack architectures: ingestion, warehouse, transformation, orchestration, reverse ETL.
• Knowledge of tools such as DLT, Fivetran, Airbyte (ingestion); BigQuery, Snowflake, Redshift (warehouse); DBT (transformation); Airflow or similar (orchestration).
• Strong Python programming skills with clean, testable, maintainable code and solid error handling.
• Fluency in SQL: complex queries, execution plans, cost optimisation.
• Experience with cloud data platforms, distributed processing, partitioning, cost optimisation, and data governance.
• Infrastructure‑as‑code experience (Terraform, CloudFormation, Pulumi) or equivalent.
• Adaptability in fast‑moving environments with evolving requirements.
• Understanding of DevOps principles: observability, resilience, incident response and operational excellence.

Bonus Points

• Experience with declarative ELT frameworks, GCP ecosystem (BigQuery, Cloud Run, Pub/Sub, Dataflow), Kafka or other event streaming platforms; scaling data systems from 0 to 100 M+ events/day; data quality frameworks such as Great Expectations, dbt tests, custom monitoring.
• Background in fintech or high‑stakes data reliability environments where data quality directly impacts revenue.
• Experience working with distributed, asynchronous teams across time zones; experience in Indian tech ecosystem or building in resource‑constrained environments; migration from legacy infrastructure to modern cloud‑native stacks.

Career Development

Career development is important to us, with progression opportunities for both individual contributors and people managers.

Equal Opportunity

Liberis is an equal opportunities employer. We welcome applications from all candidates, including individuals with disabilities and provide reasonable adjustments as required.

Hybrid Working

Our hybrid working policy requires team members to be in the office at least 3 days a week, while embracing flexibility as part of our culture.