Data Engineer

We are seeking a driven and hands-on

Data Engineer with 12 to 20 months of experience to support modern data pipeline development and transformation initiatives. The role requires solid technical skills in

SQL ,

Cloud Warehousing ,

Python , and

PySpark , with exposure to cloud platforms such as

GCP (GCS, GCC, BQ, Dataflow), dbt (cloud). As a Data Engineer at Tredence, you will work on migrating, ingesting, processing, and modeling large-scale data, implementing scalable data pipelines / topics / procedures / orchestration workflows, and applying foundational data warehousing principles. This role also includes direct collaboration with cross-functional teams and client stakeholders.

Key Responsibilities

• Develop robust and scalable

data pipelines using

PySpark in cloud platforms like

GCP Databricks Dataflow .

• Write optimized

SQL queries for data transformation, analysis, and validation.

• Implement and support data warehouse models and principles, including:
• Fact and Dimension modeling
• Star and Snowflake schemas
• Slowly Changing Dimensions (SCD)
• Change Data Capture (CDC)
• Audit Trails
• Data Quality Rules
• Medallion Architecture
• Monitor, troubleshoot, and improve pipeline performance and data quality.
• Work with teams across analytics, business, and IT functions to deliver data-driven solutions.
• Communicate technical updates and contribute to sprint-level delivery.