Who is this for :

If building scalable data infrastructure excites you, this is the place to be. Fornax is a team of cross-functional individuals who solve critical business challenges using analytics and innovative data solutions.

We are seeking a skilled Data Engineer to work on our cutting-edge data product.

The ideal candidate will possess strong technical expertise in up-to-date data stack technologies and a passion for building robust, scalable data platforms.

The Data Engineer will play a critical role in architecting, developing, and maintaining our data product infrastructure. This role involves working closely with data scientists, analytics engineers, and product stakeholders to build high-performance data pipelines, optimize query performance, and deliver reliable data solutions. The ideal candidate has a strong background in data engineering, distributed systems, and modern data tooling.

Key Responsibilities

Data Infrastructure & Pipeline Development (50%)

Design, build, and maintain scalable data pipelines using Prefect for orchestration and workflow management

Implement ELT processes using Dlthub to efficiently load data from various sources into the data platform

Develop and optimize data transformation workflows using DBT to ensure clean, modeled, and business-ready datasets

Build and manage Apache Iceberg table formats to enable efficient data lakehouse operations with ACID transactions

Leverage DuckDB for fast local analytics, development testing, and embedded analytical workloads

Ensure data pipeline reliability, monitoring, and error handling with comprehensive logging and alerting mechanisms

Query Optimization & Performance Engineering (20%)

Design and optimize distributed query execution using Trino for high-performance analytics across diverse data sources

Utilize DuckDB for rapid prototyping,



local query testing, and in-process analytical operations

Implement query optimization strategies including partition pruning, predicate pushdown, and materialized views

Monitor and tune query performance to ensure sub-second response times for critical business queries

Develop best practices for efficient data access patterns and resource utilization across different query engines

Data Modeling & Architecture (15%)

Implement semantic layer and metrics definitions for consistent business logic across applications

Design dimensional models and data mart architectures to support analytics and reporting use cases

Collaborate with analytics engineers and stakeholders to translate analytical requirements into optimized data structures

Establish and maintain data modeling standards and documentation for the data product

Data Quality & Governance (10%)

Implement data quality frameworks and validation checks within DBT models and Prefect workflows

Develop automated data testing and monitoring solutions to ensure data accuracy and consistency

Document data lineage, schema definitions, and transformation logic to maintain data governance standards

Establish SLAs for data freshness, quality, and pipeline reliability

Collaboration & Product Development (5%)

Work closely with product managers, data scientists, and business stakeholders to understand data product requirements

Participate in technical design reviews and contribute to architectural decisions

Provide technical guidance and mentorship to junior team members

Stay current with emerging technologies and best practices in the data engineering ecosystem

Requirements

Experience

3+ years of experience in data engineering or related roles

Proven track record of building and maintaining production data pipelines

Experience working on data products or platform teams

📌 Data Engineer (Mumbai)
🏢 Fornax
📍 Mumbai