This role is for one of the Weekday's clients

Min Experience: 3 years

Location: Remote (India)

JobType: full-time

We are seeking a highly motivated and detail-oriented Snowflake Data Engineer to join our data engineering team. The ideal candidate will have a strong background in Snowflake, DBT, ETL processes, and modern Lakehouse architecture, along with hands-on experience in SnapLogic and Python. You will be responsible for designing, developing, and optimizing data pipelines that support business intelligence, analytics, and reporting needs across the organization. This role requires a blend of technical expertise, problem-solving skills, and the ability to work collaboratively in a fast-paced environment.

Requirements

Key Responsibilities

Data Modeling & Warehousing: Design, implement, and optimize scalable data models and data warehouses using Snowflake to meet analytical and business requirements.
ETL Development: Build, maintain, and optimize ETL/ELT pipelines with SnapLogic, DBT, and Python, ensuring efficient ingestion and transformation of structured and unstructured data.
Lakehouse Architecture: Contribute to the development of a modern Lakehouse architecture, enabling unified data storage and advanced analytics.
Performance Optimization: Monitor, troubleshoot, and fine-tune queries, pipelines, and workflows to ensure high performance and reliability.
Automation & Integration: Develop reusable frameworks for automation of data workflows, orchestration, and integration with enterprise systems.
Data Quality & Governance: Implement data validation, error handling, and monitoring mechanisms to ensure data accuracy, integrity, and compliance with governance policies.
Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand requirements and deliver solutions that meet organizational goals.
Documentation & Best Practices: Maintain clear documentation of designs, workflows, and processes while advocating best practices for data engineering.

Required Skills & Qualifications

3 – 5 years of professional experience in data engineering or data warehousing roles.
Strong expertise in Snowflake, including performance tuning, query optimization, and warehouse management.
Proficiency in DBT (Data Build Tool) for modeling, transformations, and version-controlled data workflows.
Hands-on experience with ETL/ELT pipeline design using SnapLogic or similar tools.
Solid understanding of Lakehouse architecture and modern data platform concepts.
Strong programming skills in Python for data transformation, automation, and API integrations.
Knowledge of SQL and advanced query writing for analytics and reporting.
Familiarity with data governance, data security, and compliance frameworks.
Strong problem-solving skills with the ability to analyze complex data challenges and propose effective solutions.
Excellent communication and collaboration skills, with the ability to work in cross-functional teams.

Preferred Qualifications

Experience with cloud platforms such as AWS, Azure, or GCP.
Exposure to orchestration tools such as Airflow, Prefect, or Dagster.
Familiarity with CI/CD pipelines for data engineering.
Experience working in an agile, fast-paced product or data-driven organization.