Data Engineer (L2)

Prescienceds; Bengaluru; On-site; INR 800,000 - 1,200,000; Full time

Job summary

A data engineering firm in Bangalore is seeking a skilled Data Engineer to enhance a modern data platform using Snowflake and DBT. The role entails developing and maintaining data pipelines, with a strong focus on SQL, PySpark, and Python tools. Candidates should have at least 2 years of experience and a Bachelor’s degree in Computer Science. This position offers opportunities for professional growth in a collaborative environment.

Qualifications

• Minimum 2 years of experience as a Data Engineer or ETL Developer.
• Strong proficiency in SQL, PySpark, and Python data libraries.
• Hands-on experience with Snowflake and data warehousing concepts.

Responsibilities

• Develop and maintain high-quality ETL/ELT pipelines using Snowflake and DBT.
• Implement data ingestion patterns across multiple data sources.
• Participate in all phases of the software development lifecycle.

Skills

SQL

PySpark

Python data libraries (Pandas, NumPy)

Snowflake

AWS/Azure

Agile methodologies

Education

Bachelor’s degree in Computer Science or related field

Tools

DBT

ETL/ELT pipelines

Job description

Prescience Decision Solutions | Full time

Prescience Decision Solutions, established in 2017, partners with Fortune 500 and mid-sized companies globally to unlock enterprise data and drive improved decision-making. We specialize in Data Science, Advanced Analytics, and Data Engineering, integrating AI and machine learning to deliver measurable business value and ROI.

Headquartered in Bangalore, our ‘Business Backward’ approach ensures a deep understanding of your challenges, enabling us to provide tailored, impactful solutions.

Founded by industry leaders from IIT and IIM, Prescience is a bootstrapped and profitable company with a strong project pipeline.

Our commitment to excellence has earned us recognition as one of the top three startups in the People Excellence category by xto10x, with a 97 percentile employee NPS, 100% mutual respect among employees, and a 98% employee pride rate.

As an equal opportunity employer, we are dedicated to fostering a diverse and inclusive workplace, free from discrimination based on caste, religion, gender, sexual orientation, nationality, or other protected characteristics.

To learn more, subscribe to our YouTube channel: YouTube Link.

Role Overview

We are looking for a skilled Data Engineer to help build and enhance a modern, scalable data platform powered by Snowflake and DBT. The candidate needs to have hands‑on experience with Snowflake, DBT, and Python‑based data processing tools such as PySpark, Pandas, and NumPy. This role will focus on designing efficient data pipelines, implementing data models, and ensuring reliable data flows across the platform.

Job Description

We are looking for a skilled Data Engineer to help build and enhance a modern, scalable data platform powered by Snowflake and DBT. The candidate needs to have hands‑on experience with Snowflake, DBT, and Python‑based data processing tools such as PySpark, Pandas, and NumPy. This role will focus on designing efficient data pipelines, implementing data models, and ensuring reliable data flows across the platform.

Key Responsibilities:

1. Develop, test, document, and maintain high-quality ETL/ELT pipelines using Snowflake and DBT.
2. Implement both full-load and incremental data ingestion patterns across multiple data sources.
3. Write clean, reusable, and scalable SQL and PySpark code to support data transformations and analytics workflows.
4. Participate in all phases of the software development lifecycle, including solution design, coding, testing, deployment, and optimization.
5. Diagnose, debug, and troubleshoot pipeline or code-related issues to ensure reliable data processing.

Required Skills and Qualifications:

1. Minimum 2 years of professional experience as a Data Engineer or ETL Developer with demonstrable project experience.
2. Bachelor’s degree in Computer Science, Software Engineering, or a related field.
3. Strong proficiency in SQL, PySpark, and Python data libraries such as Pandas, NumPy, and SciPy.
4. Hands‑on experience with Snowflake and good understanding of data warehousing concepts.
5. Experience working with AWS, Azure, or another major cloud platform, with exposure to cloud‑based data services.
6. Familiarity with agile methodologies, including sprint‑based development practices.

Additional Skills and Qualifications:

1. Exposure to big data technologies (e.g., Spark, Kafka, Hadoop).
2. Understanding of data science and machine learning concepts, tools, and workflows.