We are seeking a Senior Data Scientist / Data Science Engineer with strong hands-on expertise in data pipelines, data warehousing, and analytics engineering, combined with deep Python proficiency for ETL and data services. We are looking at a candidate with 4+ years of experience, who is deeply hands-on.

This role sits at the intersection of data engineering, analytics, and applied data science. You will design, build, and operate scalable data platforms, enable analytics and dashboards, and work closely with product, engineering, and business stakeholders to translate business problems into reliable data solutions.

Machine Learning and MLOps exposure is an advantage, but strong fundamentals in data pipelines, analytics, and business understanding are mandatory.

Key Responsibilities :

Data Engineering & Pipelines :

- Design, build, and maintain robust, scalable data pipelines for structured and semi-structured data

- Develop and optimize ETL/ELT workflows using Python for batch and near-real-time processing

- Ingest data from databases, APIs, and external systems while ensuring data quality, consistency, and reliability

- Monitor pipeline health, performance, and failures; perform root cause analysis and remediation

Data Platforms & Warehousing :

- Manage and optimize data warehouses and analytical stores (Postgres, BigQuery, Snowflake)

- Strong understanding of OLTP vs OLAP, columnar storage, query optimization, and analytical modeling

- Work with cloud data platforms and tools such as BigQuery, Snowflake, Matillion (good to have)

- Support data migrations, schema evolution, and platform scaling

Python & Data Services :

- Strong hands-on Python experience for :

- ETL jobs and data transformations

- Database integrations using psycopg, SQLAlchemy, pymongo

- Data validation using Pydantic

- Performance optimization using multiprocessing/concurrency

- Build and maintain REST APIs for data access and integration using Python (FastAPI preferred)

Analytics & Dashboards :

- Perform Exploratory Data Analysis (EDA) and data preprocessing to support analytics and insights

- Build and enable business-critical dashboards and metrics

- Strong proficiency in Metabase for analytics and visualization

- Write optimized Postgres and MongoDB queries to support analytical use cases

Collaboration & Business Alignment :

- Work closely with product, engineering, analytics, and business teams to understand data requirements

- Translate business problems into data models, metrics, and actionable insights

- Promote best practices in data engineering, analytics, and automation

Optional/Good To Have :

- Exposure to Machine Learning workflows, feature preparation, and model consumption

- Understanding of MLOps concepts (model lifecycle, monitoring, versioning, deployment)

- Familiarity with CI/CD and data pipelines using GoCD

- Experience with Dockerized data workloads

Required Skills & Experience :

Must Have :

- 6+ years of experience in data engineering / data science / analytics engineering roles

- Strong Python proficiency for ETL, APIs, and data processing

- Hands-on experience with :

a. Postgres and MongoDB (querying and optimization)

b. Pandas and data preprocessing

c. REST API development in Python

- Solid understanding of :

a. Data warehousing concepts

b. OLTP vs OLAP systems and columnar storage

c. EDA and analytics fundamentals

- Proven experience building dashboards and analytics for business stakeholders, using Metabase

- Comfortable working in a fast-changing, high-ownership environment with frequent releases

Good To Have :

- BigQuery, Snowflake, Matillion

- MLOps exposure

- Docker, GoCD

- Experience working with ML pipelines or applied ML systems

What We Look For :

- Strong data fundamentals and execution mindset

- Ability to balance engineering rigor with business urgency

- Comfortable operating in ambiguity and evolving requirements

- Clear communicator who understands that data accuracy and trust directly impact business outcomes

Work Mode & Location :

- This is a full-time, onsite role

- Location : Chennai

- Candidates must be comfortable working from the office in a fast-paced, collaborative environment with frequent releases and evolving requirements