Job Description

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines that power analytics, reporting, and data-driven products. In this role, you will work closely with analytics, product, and engineering teams to ensure high-quality, reliable, and well-modeled data across the organization.

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines to ingest, transform, and curate data from multiple sources
• Build and optimize data workflows using Python, SQL, and Apache Spark
• Develop scalable batch and streaming data solutions
• Ensure data quality, reliability, and performance through monitoring, testing, and validation
• Optimize queries, data models, and storage for performance and cost
• Collaborate with data analysts, data scientists, and software engineers to support analytics and machine learning use cases
• Document data pipelines, schemas, and best practices
• Troubleshoot and resolve data pipeline failures and performance issues

Required Qualifications

• Strong experience with Python for data processing and automation
• Advanced SQL skills, including complex queries and performance tuning
• Hands-on experience with Apache Spark (PySpark preferred)
• Solid understanding of ETL/ELT concepts, data modeling, and data warehousing
• Experience working with large datasets and distributed systems
• Familiarity with version control (Git) and CI/CD practices

Preferred Qualifications

• Experience with cloud data platforms (AWS, GCP, or Azure)
• Work with Azure synapse and Fabric
• Familiarity with orchestration tools (e.g., Airflow, Dagster, Prefect)
• Experience with modern data warehouses
• Knowledge of data quality frameworks and monitoring tools

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