Data Engineer

Job Description

Job Title: Data Engineer Experience: 12 to 20 months Work Mode: Work from Office Locations: Bangalore, Chennai, Kolkata, Pune, Gurgaon Role Overview 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 , Python , and PySpark , with exposure to cloud platforms such as Azure Databricks or GCP . As a Data Engineer at Tredence, you will work on ingesting, processing, and modeling large-scale data, implementing scalable data pipelines, 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 Azure Databricks or GCP 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) 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. Mandatory Skills Strong hands-on experience with SQL and Python Working knowledge of PySpark for data transformation Exposure to at least one cloud platform: Azure Databricks or GCP Good understanding of data engineering and warehousing fundamentals Excellent debugging and problem-solving skills Strong written and verbal communication skills Preferred Skills Experience working with Databricks Community Edition or enterprise version Familiarity with data orchestration tools like Airflow or Azure Data Factory Exposure to CI/CD processes and version control (e.g., Git) Understanding of Agile/Scrum methodology and collaborative development Basic knowledge of handling structured and semi-structured data (JSON, Parquet, etc.)