Senior Data 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 and data infrastructure supporting analytics, reporting, and AI/ML initiatives.
- Build and maintain data models, warehouses, and semantic layers on cloud platforms (AWS, GCP, Azure) using tools like Airflow, dbt, or Data Factory.
- Collaborate with Data Architects, Scientists, and business stakeholders to translate requirements into technical solutions and ensure data quality and governance.
Minimum Requirements
- 4 to 10 years of relevant Data Engineering or related experience.
- Proficiency in advanced SQL, Python and/or PySpark, and experience with cloud data platforms and associated data warehouse/lake services (Snowflake, BigQuery, Databricks, Microsoft Fabric).
- Hands-on experience with workflow orchestration tools such as Airflow, dbt, Cloud Composer, or Data Factory.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience.
Ideal Candidate Profile
- Experienced in end-to-end ownership of cloud-native data pipelines and strong problem-solving in data engineering context.
- Able to collaborate effectively with cross-functional teams including technical and non-technical stakeholders.
- Prior exposure or interest in advanced data engineering domains such as MLOps, unstructured data/GenAI, or BI enablement is a plus but not mandatory.