Data Analyst 3

Job Description: Data Engineer Interview Rounds : 1 round of interview Location : Santa Clara, CA Contract : 4 Months + We are seeking a skilled Data Application Engineer to design, build, and maintain data-driven applications and pipelines that enable seamless data integration, transformation, and delivery across systems. The ideal candidate will have a strong foundation in software engineering, database technologies, and cloud data platforms, with a focus on building scalable, robust, and efficient data applications. Key Responsibilities: Develop Data Applications: Build and maintain data-centric applications, tools, and APIs to enable real-time and batch data processing. Data Integration: Design and implement data ingestion pipelines, integrating data from various sources such as databases, APIs, and file systems. Data Transformation: Create reusable ETL/ELT pipelines to process and transform raw data into consumable formats using tools like Snowflake, DBT, or Python. Collaboration: Work closely with analysts, and stakeholders to understand requirements and translate them into scalable solutions. Documentation: Maintain comprehensive documentation for data applications, workflows, and processes. Required Skills and Qualifications: Education: Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience). Programming: Proficiency in programming languages Python, C# , ASP.NET (Core) Databases: Strong understanding of SQL, database design, and experience with relational (e.g., Snowflake, SQL Server) databases Data Tools: Hands-on experience with ETL/ELT tools and frameworks such as Apache Airflow (DBT - Nice to Have) Cloud Platforms: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud, and their data services (e.g., S3, AWS Lambda etc.). Data Pipelines: Experience with real-time data processing tools (e.g., Kafka, Spark) and batch data processing. APIs: Experience designing and integrating RESTful APIs for data access and application communication. • Version Control: Knowledge of version control systems like Git for code management. • Problem-Solving: Strong analytical and problem-solving skills, with the ability to troubleshoot complex data issues. Preferred Skills: Knowledge of containerization tools like Docker and orchestration platforms like Kubernetes. Experience with BI tools like Tableau, Power BI, or Looker. Soft Skills: Excellent communication and collaboration skills to work effectively in cross-functional teams. Ability to prioritize tasks and manage projects in a fast-paced environment. Strong attention to detail and commitment to delivering high-quality results. #TB\_EN #ZR