Job Description/Responsibilities

Design, develop, and maintain Solutions using Snowflake and modern ELT tools (Matillion & ADF fabrics).

Build and optimize Snowflake Applications, schemas, tables, and data models.

Develop and maintain ELT workflows to ingest data from multiple sources (APIs, databases, files, streaming).

Implement data transformation and cleansing using SQL, Snowflake tasks, and stored procedures.

Optimize query performance, storage, and compute usage in Snowflake.

Manage data security, governance, and access control within Snowflake.

Collaborate with data analysts, BI teams, and data scientists to deliver reliable datasets.

Collaborate with data engineers, analysts, and stakeholders to define data requirements and create robust data pipelines.

Optimize performance of Snowflake through clustering, caching, query tuning, and cost management.

Oversee data integration strategies from multiple sources (APIs, databases, flat files, third-party platforms).

Monitor and troubleshoot data pipeline failures and performance issues.

Implement data quality checks, validation, and monitoring.

Perform code reviews whenever needed to ensure standardization and quality

Deliver 2nd level support as required

Required Qualifications

5+ years of experience in data engineering, architecture, or similar roles.

Proficient in Snowflake (multi-cluster warehouse design, role-based access, data sharing, Cloud Data Platform etc.).

Proficient in designing and implementing pipelines with ELT tools (Matillion & ADF fabrics).

Proficient in data modeling and building scalable cloud data platforms such as Azure

Strong SQL and scripting (e.g., Python or Bash) skills.

Hands-on experience with cloud platforms (Azure).

Familiar with CI/CD, version control (Git) and DevOps practices.

Preferred Qualifications

Experience with dbt, Airflow, or other orchestration and transformation tools.

Knowledge of BI/reporting tools (e.g., Power BI, Tableau, Looker).

Familiarity with data governance and data catalog solutions

Background in supporting machine learning platforms and real-time data pipelines.

Industry experience in [finance, commercial, retail, etc. can be customized].

Skills

• Applications
• Architecture
• Designing
• Engineering
• Machine Learning
• Modeling
• Python
• Security
• SQL
• Tools