Being a Data Engineer with Xtremax means more than just moving data around—you’ll help design, build, and maintain the pipelines and systems that power our products and analytics. You’ll work closely with architects, analysts, and developers to transform raw data into meaningful insights and scalable solutions.
Responsibility
- Data Design & Design
- Design, develop, and deploy data tables, views, and marts across data warehouses, operational data stores, data lakes, and data virtualization platforms.
- Perform data extraction, cleaning, transformation, and flow, including web scraping when required.
- Build and maintain large-scale batch and real-time data pipelines using data processing frameworks.
- Integrate and collate data silos in a scalable and compliant manner.
- Collaboration & Delivery
- Work closely with Project Managers, Data Architects, Business Analysts, Frontend Developers, Designers, and Data Analysts to deliver data-driven products.
- Develop backend APIs and work on databases to support applications.
- Participate in pair programming and code reviews to ensure code quality and reliability.
- Work in an Agile environment practicing Continuous Integration and Delivery.
Must-Have
- Strong proficiency in data cleaning and transformation (e.g., SQL, pandas, R).
- Must have 3 yearsor moreof relevant experience.
- Hands-on experience with ETL pipeline tools/frameworks (e.g., SSIS, AWS DMS, AWS Lambda, Glue, ECS, EventBridge, Python, Spring).
- Proficient in database design and experience with multiple databases (e.g., SQL, PostgreSQL, MySQL, MongoDB, Cassandra, SQLite, VoltDB, AWS S3, Athena, Postgres/GIS).
- Familiarity with big data frameworks and tools (e.g., Hadoop, Spark, Kafka, RabbitMQ).
- Solid understanding of system design, data structures, and algorithms.
- Comfortable with at least one scripting language (e.g., Python, SQL).
- Experience working in both Windows and Linux environments.
Nice to Have
- Cloud experience with AWS, Azure, or Google Cloud.
- Familiarity with data modeling, data marts, data lakes, virtualization, and warehouses.
- Experience with REST APIs and web protocols.
- Exposure to web scraping frameworks/tools (e.g., BeautifulSoup, Selenium, PhantomJS, Node.js).
- Knowledge of data governance policies, access control, and security best practices.
- Interest in bridging engineering and analytics.
Certificate Preferred
- AWS Certified Data Analytics – Specialty
- Google Cloud Professional Data Engineer
- Microsoft Azure Data Engineer Associate
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