Data Engineer

Exillar Infotech Pvt Ltd; Ahmedabad District; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Diverse data challenges

Cross‑functional collaboration

Growth opportunities

Engineering culture

Job summary

Exillar Infotech Pvt Ltd, based in Ahmedabad, is seeking a skilled Data Engineer to build and maintain data infrastructure powering analytics and AI workloads. You will collaborate with BI, AI/ML teams and stakeholders to ensure reliable, pipeline‑ready data across systems.

The role emphasizes scalable pipeline design, data quality, and governance, with opportunities to work on modern data lakes and warehouses in a fast‑growing tech environment.

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.

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.

Skills

Python

SQL

ETL/ELT tools

Cloud platforms

Data warehousing

Big data

Data modeling

Git

Education

Bachelor's degree in Computer Science or IT

Tools

Apache Airflow

dbt

Azure Data Factory

Azure Synapse

Snowflake

BigQuery

Redshift

Databricks

Kafka

Job description

Exillar is an Ahmedabad-based technology company specializing in Business Intelligence, Data Engineering, and AI-powered solutions. We partner with businesses to build scalable data infrastructure, modern data pipelines, and intelligent systems that turn raw data into strategic advantage.

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 andtransformation challenges at scale – and takes pride in building systems that others canrely 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 findssatisfaction 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