Data Engineer - Snowflake and DBT

Job Requirements Job Description

Required Qualifications

• Bachelor's or master's degree in computer science, engineering, mathematics or a

related discipline, or equivalent practical experience.

• Substantial professional experience designing and operating enterprise data pipelines

and data warehouses in production.

• Advanced SQL skills and strong hands-on experience with Python and/or PySpark for

data processing and automation.

• Deep experience with Snowflake, including performance optimization, security, workload

management and scalable data modeling.

• Experience building ETL/ELT solutions with dbt, Informatica PowerCenter or comparable

transformation and integration tools.

• Hands-on experience implementing CI/CD pipelines for data engineering workloads

using Git-based workflows and automated testing/deployment tools.

• Experience building automated data quality systems with measurable rules, alerting,

lineage and issue-resolution workflows.

• Strong grounding in data profiling, cleansing, standardization, reconciliation and

production data validation.

• Ability to gather ambiguous requirements, make sound design decisions and

communicate effectively with technical and non-technical partners.

Preferred Qualifications

• Snowflake SnowPro Core or comparable cloud data certification.
• Experience with REST API, event and/or streaming data, and high-volume security or

operational datasets.

• Familiarity with data observability and quality frameworks such as dbt tests, Great

Expectations, Soda or Deequ.

• Experience delivering data solutions in regulated, security-sensitive, healthcare,

telecommunications or audit-oriented environments.

• Demonstrated technical leadership, mentoring or delivery coordination across a small

engineering team.

Education Qualificaiton

B Tech/ M Tech

Recruiters

Roles & Responsibilities

• Design and deliver scalable pipelines. Build batch and near-real-time ETL/ELT pipelines using

SQL, Python and PySpark, with Snowflake as a primary cloud data platform.

• Engineer reliable data models. Create dimensional, normalized and analytical models that support

efficient querying, traceability and reuse across enterprise reporting and analytics.

• Own data quality by design. Implement automated profiling, sc

Work Experience 5-7Years