Senior Data Engineer

Quantiphi Analytics Solutions; Gurugram District; Hybrid; INR 1,500,000 - 2,800,000; Full time

Job summary

Quantiphi Analytics Solutions in Gurugram invites a Senior Data Engineer with 5+ years of hands-on experience to build and optimize data pipelines. You will work with SQL, Python, DBT, Snowflake, and AWS to deliver robust data models and reliable ETL processes.

The role emphasizes data warehousing best practices, star schemas, and Snowflake features like streams and tasks. Daily ingestion from diverse sources, orchestration with Airflow/Argo, and collaboration with asset management or financial

Qualifications

• 5+ years of hands-on data engineering experience.
• Strong SQL, Python, DBT and Snowflake expertise.
• Experience with AWS services and data modelling.

Responsibilities

• Design and maintain data pipelines using Snowflake and AWS.
• Push data to the golden layer using Snowflake streams and stored procedures.
• Work with data modeling concepts like star schema and SCD types.
• Coordinate with teams; set up DAGs with Airflow/Argo.
• Manage ingestion from external sources via SFTP and Snowflake share.

Skills

SQL

Python

DBT

AWS

Data modelling

Snowflake

Data pipelines

Troubleshooting

Unix/Linux basics

Git

Tools

Airflow

Argo Workflows

Snowflake Workflows

Snowflake Tasks

AWS S3

Lambda

Redshift

EventBridge

Job description

Role: Senior Data Engineer

Experience Level: 5+ Years

Work location: Gurugram

Role & responsibilities:

• Strong proficiency in SQL, Python, DBT, AWS services, data modelling, Snowflake, building and maintaining data pipelines, and robust troubleshooting capabilities.
• In addition, exposure to asset management, alternative investments, or broader financial domain knowledge is highly valuable.
• Experience in establishing a golden source of truth using Snowflake as the data warehousing tool, with current data sources coming from external sources via SFTP and SEI via a Snowflake share, the data engineer's role involves pushing data to the golden layer using Snowflake tools like streams and stored procedures, requiring strong SQL stored procedure and Python skills, as well as a good understanding of data modeling concepts like star schema.
• AWS resources on the data side needed and not on the infra side & same for Snowflake.
• Exposure to orchestration tool on Data engineering side, so that they can setup date pipeline etc
• Seeking a hands-on engineer with five to six years of experience and knowledge of basic AWS services like Redshift and S3.
• Data Ingestion, Frequency, and Orchestration The team is currently unsure of the exact frequency of files from JPMC but expects them to be on a daily or monthly basis, with transaction files potentially having a daily frequency Tools: AWS S3, AWS Lamda, SNS, SQS.
• Orchestrating third-party feeds, they plan to use Snowflake workflows and jobs, but for other projects, Tools : they might use external orchestration tools like Argo workflows and Airflow and snowflake task
• Snowflake: Role requires a person with a good understanding of different data models (Relational, Dimensional, Star Schema, SCD Types). The team is moving away from JavaScript procedures and is using SQL stored procedures within Snowflake. Tools: Snowflake Share, snowflake architecture (micro partition) , snowflake best practices, Snowflake SQLs, snowflake procedures, UDF, Task
• Other Tools: Python is definitely a required skill, and basic knowledge of Unix and Linux is good to have for using tools like Git. Data streams are used for change tracking purposes within Snowflake.
• Looking for a hands-on person with around five to six years of experience and no architecture experience is required because that is already completed. The required AWS skills include knowledge of basic services such as Redshift, EventBridge.