Senior AI Engineer
LatentView Analytics (company site, opens in a new tab)4–10 yrsChennaiOn-siteDirect career pageEst. 12–22 LPA
Posted on 10 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable ETL/ELT data pipelines for diverse data sources supporting analytics and AI/ML initiatives.
- Build and optimize data models, warehouses, and automate data workflows on cloud platforms such as AWS, GCP, or Azure.
- Collaborate with Data Architects, Scientists, and business teams; troubleshoot data quality and pipeline performance; mentor junior engineers (scope depends on seniority).
Minimum Requirements
- 4–10 years of experience in Data Engineering or related roles.
- Proficient in advanced SQL, Python and/or PySpark for data processing and automation.
- Experience with cloud data platforms (AWS, GCP, or Azure) and data warehouse/lake technologies (Snowflake, BigQuery, Databricks, Microsoft Fabric).
- Degree in Computer Science, Engineering, or related quantitative field, or equivalent practical experience.
Ideal Candidate Profile
- Experienced in end-to-end ownership of cloud-native data engineering pipelines and workflow orchestration tools like Airflow, dbt, or Cloud Composer.
- Able to work cross-functionally with technical and business stakeholders to translate requirements into scalable data solutions.
- Has prior exposure to advanced data engineering domains such as Marketing/Media data, GenAI adjacent engineering, Databricks DataOps, Microsoft Fabric, or team leadership roles for mentoring and delivery ownership.