Website:
iaretes.in
Job details:
Company Description iAretes is a Data Engineering, AI/ML, and Agents Studio based in Chennai, India, focused on delivering production-grade systems rather than strategy documents. The team designs and builds robust data pipelines, lakehouse architectures, and cloud infrastructure using modern tools such as PySpark, Airflow, dbt, Apache Iceberg, Delta Lake, and AWS-native services. iAretes also creates real-time streaming solutions, AI agents, and LLM/RAG applications that integrate seamlessly into client workflows. They emphasize end-to-end ownership, with the same engineers handling architecture, coding, CI/CD, and deployment, supported by clean documentation and knowledge transfer so clients can operate systems independently. Their track record includes significant performance improvements, such as reducing pipeline processing times by up to 99%.
Role Description This is a full-time hybrid Data Engineer role based in Coimbatore, with flexibility for some work from home. The Data Engineer will design, build, and maintain scalable data pipelines and ETL processes to support analytics, AI/ML, and application workloads. Responsibilities include modeling data for lakehouse and warehousing solutions, optimizing performance and reliability, and ensuring data quality and integrity across systems. The role involves collaborating closely with engineering and product teams to translate business needs into technical solutions, implement monitoring and automation, and contribute to documentation and best practices. The Data Engineer will also participate in code reviews, CI/CD workflows, and continuous improvement of data infrastructure.
Qualifications
- Strong skills in Data Engineering and Extract Transform Load (ETL) for building and managing production data pipelines.
- Proficiency in Data Modeling and Data Warehousing to design structured, scalable storage and retrieval solutions.
- Experience with Data Analytics to support reporting, dashboards, and data-driven decision-making.
- Hands-on experience with modern data technologies (e.g., SQL, Python, Spark, Kafka, cloud platforms such as AWS, Azure, or GCP) is highly beneficial.
- Solid understanding of software engineering practices, including version control, testing, and CI/CD.
- Ability to work in a hybrid setup, collaborate effectively with cross-functional teams, and communicate complex technical concepts clearly.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
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