Job Description

Data Analytics Engineer Job Description Job Title: Data Analytics Engineer Experience: 3 to 6 years Location: Gurgaon (Hybrid) Employment Type: Full-time Job Description: We are seeking a highly skilled Data Analytics Engineer with expertise in Qlik Replicate, Qlik Compose, and Data Warehousing to build and maintain robust data pipelines. The ideal candidate will have hands-on experience with Change Data Capture (CDC) pipelines from various sources, an understanding of Bronze, Silver, and Gold data layers , SQL querying for data warehouses like Amazon Redshift , and experience with Data Lakes using S3 . A foundational understanding of Apache Parquet and Python is also desirable. Key Responsibilities: 1. Data Pipeline Development & Maintenance Design, develop, and maintain ETL/ELT pipelines using Qlik Replicate and Qlik Compose. Ensure seamless data replication and transformation across multiple systems. Implement and optimize CDC-based data pipelines from various source systems. 2. Data Layering & Warehouse Management Implement Bronze, Silver, and Gold layer architectures to optimize data workflows. Design and manage data pipelines for structured and unstructured data . Ensure data integrity and quality within Redshift and other analytical data stores. 3. Database Management & SQL Development Write, optimize, and troubleshoot complex SQL queries for data warehouses like Redshift . Design and implement data models that support business intelligence and analytics use cases. 4. Data Lakes & Storage Optimization Work with AWS S3-based Data Lakes to store and manage large-scale datasets. Optimize data ingestion and retrieval using Apache Parquet . 5. Data Integration & Automation Integrate diverse data sources into a centralized analytics platform. Automate workflows to improve efficiency and reduce manual effort. Leverage Python for scripting, automation, and data manipulation where necessary. 6. Performance Optimization & Monitoring Monitor data pipelines for failures and implement recovery strategies. Optimize data flows for better performance, scalability, and cost-effectiveness . Troubleshoot and resolve ETL and data replication issues proactively. Technical Expertise Required: 3 to 6 years of experience in Data Engineering, ETL Development, or related roles. Hands-on experience with Qlik Replicate & Qlik Compose for data integration. Strong SQL expertise, with experience in writing and optimizing queries for Redshift . Experience working with Bronze, Silver, and Gold layer architectures . Knowledge of Change Data Capture (CDC) pipelines from multiple sources. Experience working with AWS S3 Data Lakes . Experience working with Apache Parquet for data storage optimization. Basic understanding of Python for automation and data processing. Experience in cloud-based data architectures (AWS, Azure, GCP) is a plus. Strong analytical and problem-solving skills. Ability to work in a fast-paced, agile environment . Preferred Qualifications: Experience in performance tuning and cost optimization in Redshift. Familiarity with big data technologies such as Spark or Hadoop. Understanding of data governance and security best practices . Exposure to data visualization tools such as Qlik Sense, Tableau, or Power BI.