Job Summary:

We are seeking a highly skilled and visionary Data Engineer to build, and optimize our modern data architecture within the Investment and Wealth Management sector. In this role, you will develop an end-to-end scalable data pipelines, enterprise data warehousing, and advanced analytics platforms.

You will leverage a cutting-edge up-to-date data stackincluding Azure, Snowflake, dbt, Fivetran, ADF, Python, and PySparkto deliver high-quality, actionable financial data. Additionally, you will play a pivotal role in pioneering the integration of Generative AI (Gen AI) solutions to enhance financial insights, automate data workflows, and support intelligent investment strategies.

Job Responsibilities

ELT Pipeline Support

Assist in building and maintaining ELT pipelines using tools like Fivetran for data ingestion.

Work with Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS) to support secure data movement and storage for financial datasets.

Monitor pipeline runs and help troubleshoot basic issues under senior guidance.

Snowflake & dbt Development

Contribute to creating and maintaining data models in Snowflake.

Use dbt to write SQL transformations, add documentation, and perform basic testing.

Learn version control practices and collaborate with the team to ensure reliable data workflows.

Performance & Cost Awareness





Support monitoring of pipeline performance and resource usage in Snowflake and Azure.

Learn how optimization techniques (like clustering or query tuning) can improve efficiency and reduce costs.

Escalate performance concerns to senior engineers for deeper analysis.

Coding & Framework Contribution

Write clean, modular SQL queries for financial data analysis.

Use Jinja templating in dbt to create reusable code components.

Develop Python scripts or PySpark jobs for simpler data processing tasks, with mentorship for more complex work.

AI & Emerging Tools Exploration

Learn how AI and large language models (LLMs) can be applied in data engineering.

Assist in experimenting with AI driven tools that support data platform operations.

Document findings and share with the team to encourage innovation.

Required skills

- 1 - 3 years of experience in Data Engineering
- Data Engineering - Azure, Snowflake, DBT, Databricks, Gen AI, SQL, Pyspark
- Data Visualization - Power BI, Power Platform

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Analyst - Data Engineering (Chennai)
🏢 Latentview
📍 Chennai