Data Engineer

Exillar; Ahmedabad District; On-site; INR 600,000 - 1,200,000; Full time

Benefits offered by this job

Growth opportunities

Structured career path

Culture of continuous learning

Job summary

Exillar seeks a skilled Data Engineer to build and maintain data infrastructure powering analytics, reporting, and AI/ML workloads. You will collaborate with BI Devs, AI/ML Engineers, and business stakeholders to ensure data is accurate, accessible, and pipeline-ready at all times.

The role involves designing scalable pipelines, managing ETL/ELT workflows, and ensuring data quality while supporting feature delivery for analytics and AI initiatives.

Qualifications

• 2+ years of hands-on data engineering experience.
• Proficient in Python for data processing and automation.
• Strong SQL skills with complex transformations and optimization.
• Hands-on with ETL/ELT tools like Airflow, dbt, or ADF.
• Experience with cloud data platforms (Azure, AWS, or GCP).
• Familiarity with data warehousing (Azure Synapse, Snowflake, BigQuery, Redshift).
• Knowledge of big data tech (Spark, Databricks, Kafka).
• Bachelor's degree in CS/IT or related field.

Responsibilities

• Design, build, and maintain robust data pipelines (batch and streaming).
• Develop and manage ETL/ELT workflows across sources, warehouses, and consumption layers.
• Architect and optimize data warehouse and lake structures for performance and cost.
• Ensure data quality and integrity across pipelines and storage.
• Collaborate with BI to deliver clean, query-ready data.
• Work with AI/ML teams to prepare and serve feature-ready datasets.
• Monitor and optimize pipeline performance and reliability.
• Enforce data governance: lineage, cataloging, access controls, and docs.
• Evaluate tools and architectural improvements as needs evolve.

Skills

Python

SQL

Data modeling

Git

Agile/Lean

Problem solving

Education

Bachelor's degree in Computer Science or IT

Tools

Apache Airflow

dbt

Azure Data Factory

Azure Synapse

Snowflake

BigQuery

Redshift

Apache Spark

Databricks

Kafka

Docker

Kubernetes

Job description

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

Good 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