Data Engineer

As a Data Engineer at Saras Analytics, you will play a crucial role in building and maintaining scalable, reliable data pipelines and analytics-ready models. This is a hands-on, customer-facing position requiring exceptional problem-solving skills, a strong sense of ownership, and the ability to work independently with US-based clients, requiring a 35-hour overlap with US EST/CST/PST time zones.

Key Responsibilities include: developing ELT pipelines using BigQuery or Snowflake, dbt, and cloud services; writing production-grade Python code for data ingestion, transformation, and automation; designing analytics-ready data models; collaborating directly with customers to define and clarify requirements; ensuring data quality through rigorous testing, validation, and monitoring; debugging pipeline failures, data issues, and performance bottlenecks; and actively participating in code reviews while adhering to engineering best practices.

We require 2-4 years of experience in data engineering or analytics engineering. Candidates must possess strong SQL skills, including joins, CTEs, and window functions, along with hands-on experience in BigQuery or Snowflake. Proficiency in Python for production pipelines and experience with dbt (models and tests) are essential. Prior customer-facing or stakeholder-facing experience, coupled with a strong ownership and accountability mindset, is highly valued.