NC 2 Backend Engineer

Job Description for Data Engineer / Data Specialist Location: Bangalore Work Mode: Hybrid Experience: 8+ years 1. Position Summary We are looking for an experienced Data Engineer / Data Specialist with 6-8 years of hands-on experience in data preparation, data warehousing, and data platform workflows for analytics. The ideal candidate will play a crucial role in managing large datasets, ensuring data availability for analytics, and supporting business requirements gathering with strong communication skills. You will be responsible for end-to-end data handling, from preparation to loading into the data warehouse and enabling visualization teams. 2. Key Responsibilities Prepare and transform large volumes of data (millions of records) for analytics and reporting purposes. Load and monitor data into databases, primarily Postgres and Spark-based environments. Understand, maintain, and troubleshoot data pipelines, including scheduled data ingestion and job monitoring (e.g., handling job failures). Collaborate and effectively communicating with business teams to gather and understand data requirements, effectively translating requirements into data solutions as a forward deployed engineer. Coordinate with visualization and analytics teams to ensure data availability and integrity for reporting tools. Implement and enforce best practices for data preparation and curation in line with a curated data layer approach. 3. Mandatory Skills and Experience Technical Expertise: Strong experience working with large datasets (e.g., handling tables with millions of records). In-depth knowledge of data warehousing concepts, specifically experience with Postgres databases. Practical experience with Apache Spark (including PySpark), focusing on data processing within Spark clusters. Familiarity with modern data ingestion concepts, including scheduling, automated job monitoring, and troubleshooting failures. Experience working with data preparation layers rather than solely focusing on traditional ETL coding. Data preparation for consumption by data visualization tools like Tableau, with focus on data back-end support rather than report creation itself. Conceptual Understanding: Strong understanding of the differences and nuances between data platforms such as Spark and traditional databases. Familiarity with the business implications of fiscal and calendar years in analytics and reporting. Ability to communicate technical concepts clearly and interact confidently with business stakeholders. Soft Skills: Excellent communication skills for interacting closely with business teams and stakeholders for requirement gathering and fulfillment. Proactive attitude towards vetting data quality and data pipeline reliability. Detail-oriented with the ability to explain and document technical details effectively. Ability to work in a hybrid team model and collaborate with cross-functional teams. 4. Preferred…