Sr. Data Engineer

We are looking for a Data Engineer II, Analytics to join our growing team and help build scalable, high-performance data pipelines that enable meaningful business insights you'll work with modern data tools, collaborate with cross-functional teams, and contribute to building a robust data foundation that supports Eightfolds AI-driven analytics and reporting needs What You Will Learn To Do Design & Develop Pipelines: Build, maintain, and optimize reliable ETL/ELT pipelines to ingest, process, and transform large datasets from diverse sources using Databricks and Amazon Redshift Data Modeling & Architecture: Support the design and implementation of scalable data models and architectures to meet evolving analytics and business intelligence needs Data Quality & Integration: Ensure accuracy, consistency, and quality of integrated data from structured and unstructured sources across systems Performance Tuning: Optimize the performance of queries, pipelines, and databases to ensure high efficiency and reliability for analytics workloads Collaboration & Delivery: Partner with analytics engineers, data scientists, product managers, and business stakeholders to deliver high-quality data solutions that enable business insights and product innovations Documentation & Best Practices: Contribute to documentation, promote data engineering best practices, and ensure data governance, security, and compliance standards are upheld What We Need: Experience: 3-6 years of hands-on experience as a Data Engineer or in a similar data engineering role, ideally in analytics-focused environments Databricks: Practical experience building and managing pipelines and workflows using Databricks Amazon Redshift: Strong understanding of Amazon Redshift, including data modeling and query optimization Programming: Proficiency in SQL and working knowledge of Python or Scala for data processing tasks ETL/ELT Tools: Hands-on experience developing and maintaining ETL/ELT processes Big Data Tools (Good to Have): Familiarity with Apache Spark, Hadoop, Kafka, or other big data technologies is a plus Analytical & Problem-Solving Skills: Ability to troubleshoot data issues and optimize performance effectively Communication & Collaboration: Strong communication skills with a collaborative mindset in fast-paced environments