Role Overview

- We are looking for a skilled and self-driven Data Engineer to join our engineering team. In this role, you will be responsible for building and maintaining the data infrastructure that powers analytics, reporting, and AI/ML workloads.

- You will work closely with BI Developers, AI/ML Engineers, and business stakeholders to ensure data is accurate, accessible, and pipeline-ready at all times.

- This role is ideal for someone who enjoys solving complex data movement and transformation challenges at scale - and takes pride in building systems that others can rely on.

Key Responsibilities

- Design, build, and maintain robust, scalable data pipelines (batch and streaming) for ingestion, transformation, and delivery

- Develop and manage ETL/ELT workflows to move data across sources, warehouses, and consumption layers

- Architect and maintain data warehouse and data lake structures optimized for performance and cost

- Ensure data quality, consistency, and integrity across all pipelines and storage layers

- Collaborate with BI Developers to provide clean, well-modeled, query-ready data

- Work with AI/ML Engineers to prepare, version, and serve feature-ready datasets

- Monitor, troubleshoot, and optimize pipeline performance and reliability

- Implement and enforce data governance practices - lineage, cataloging, access controls, and documentation

- Evaluate and recommend tools, technologies, and architectural improvements as data needs evolve

Required Skills & Qualifications

- 2+ years of hands-on experience in data engineering or a closely related role

- Strong proficiency in Python for data processing, pipeline development, and automation

- Solid command of SQL - complex transformations, performance optimization,



and database management

- Hands-on experience with ETL/ELT tools such as Apache Airflow, dbt, Azure Data Factory, or similar

- Experience with cloud data platforms - Microsoft Azure (preferred), AWS, or GCP

- Working knowledge of data warehousing solutions - Azure Synapse, Snowflake, BigQuery, or Redshift

- Familiarity with big data technologies - Apache Spark, Databricks, or Kafka

- Understanding of data modeling concepts - normalized, dimensional, and lakehouse architectures

- Experience with version control (Git) and collaborative development practices

- Bachelor's degree in Computer Science, Information Technology, or a related field

Valuable to Have

- Exposure to real-time or streaming data pipelines (Kafka, Azure Event Hubs, or similar)

- Experience with containerization and orchestration - Docker, Kubernetes

- Familiarity with infrastructure-as-code or CI/CD practices in data environments

- Knowledge of data quality frameworks or tools (Great Expectations, Monte Carlo, etc.)

- Basic understanding of ML pipelines and feature stores

- Experience working in Agile or sprint-based delivery teams

Who Will Thrive in This Role

- Someone who is obsessed with reliability, thinks upstream before downstream, and finds satisfaction in building pipelines that simply never break.

- If you treat data as a product - not just a byproduct - this role is built for you.

What We Offer

- Work on diverse, complex, real-world data engineering challenges across industries

- Direct collaboration with BI, AI/ML, and product teams in an integrated data environment

- Structured growth path within a fast-scaling technology company
- A culture that values engineering excellence, ownership, and continuous learning

📌 Data Engineer (Ahmedabad)
🏢 Exillar
📍 Ahmedabad