Data Engineer

About the Role

We are seeking a highly experienced Data Engineer for the development and optimization of our modern cloud data platform infrastructure. This role is ideal for someone who thrives in a fast-paced environment, is passionate about data architecture, and has a deep understanding of data transformation, modeling, and orchestration using modern tools like dbt-core , Snowflake , and Python .

Key Responsibilities

• Develop and implement scalable data pipelines using dbt-core, Python, and SQL to support analytics, reporting, and data science initiatives.
• Optimize data models in Snowflake to support efficient querying and storage.
• Development and maintenance of our data warehouse , ensuring data quality, governance, and performance.
• Collaborate with cross-functional teams including data analysts, data architects, data scientists, and business stakeholders to understand data needs and deliver robust solutions.
• Develop and support the best practices SOP for version control (Git), CI/CD pipelines, and data pipeline monitoring.
• Task Ownership and Self driven , work in a culture of technical excellence and continuous improvement.
• Independently execute POC to recommend new tools and technologies to enhance the data platform.
• Provide on-going support for the existing ELT/ETL processes and procedures.
• Other duties as assigned including but not limited to possible reallocation of efforts to other organizations per business need and management request.

Required Qualifications

• Bachelor's degree in computer science or related field (16 years of formal education related to engineering)
• Around 5 years of experience in data engineering with minimum of 1+ years of experience in Snowflake and Python.
• Expert-level proficiency in SQL for data transformation and automation.
• Experience with dbt-core for data modeling and transformation.
• Strong hands-on experience in cloud platforms (Microsoft Azure) and cloud data platforms (Snowflake ).
• Proficiency with Git and collaborative development workflows. Familiarity with Microsoft VSCode or similar IDEs. Knowledge of Azure DevOps or Gitlab development operations and job scheduling tools.
• Solid understanding of modern data warehousing architecture , dimensional modeling, ELT/ETL frameworks.
• Excellent communication skills and the ability to translate complex technical concepts to non-technical stakeholders.
• Proven expertise in designing and implementing batch and streaming data pipelines to support near real-time and large-scale data processing needs.

Preferred Qualifications

• Experience working in a cloud-native environment (AWS, Azure, or GCP).
• Familiarity with data governance, security, and compliance standards.
• Prior experience with Apache Kafka (Confluent), DataOps.Live, Atlan.
• Hands-on experience with orchestration tools (e.g., Active Batch, Airflow, Prefect) is a plus.