Analyst - Data Engineering

LatentView Analytics · Chennai

Source and collection record

Last observed by our collector: 8 October 2026 at 11:39 pm IST. This is not a manual review or a confirmation from the employer.

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Collected role description

Designation : Analyst - Data EngineeringLevel : L1Location : ChennaiExperience : 3 to 4 Years Job Role :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 modern data stack—including Azure, Snowflake, dbt, Fivetran, ADF, Python, and PySpark—to 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. 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 : Data Engineering - Azure, Snowflake, DBT, Databricks, Gen AI, SQL, PysparkData Visualization - Power BI, Power Platform

Collected experience requirement

3 - 4 Years