Data Engineer (Onsite, US) at Wipro Technologies

Location: Fully Onsite in either Fremont, CA or Austin, TX*This position is a fully onsite position and not eligible for relocation.  Salary: Up to $90,000 + 10% performance bonus (DOE & Geographic Location)  About the Role:  As a Data Engineer, you will be responsible for building industry-leading, highly intuitive software products that underpin business functions across our client's enterprise applications. Candidates must be passionate about technology, live for amazing customer service, and thrive in a fast-paced environment. Our clients are Fortune 100 technology companies, providing platforms that help connect people around the world. They share a core value of scaling their businesses by putting people first, and our team is dedicated to advancing this mission by focusing on customer needs above all else.   About you:  Familiar with end-to-end Customer/IT support processes  Adjusts easily to new or changing circumstances. A collaborative utility player mentality (low ego) with a proactive sense of curiosity Focuses on achieving results that promote business success. Demonstrate proactive and professional communication skills with all stakeholders and partners Maintain a professional, adaptable, and respectful manner Provide high quality service to all users   Responsibilities:  Extensive experience with data modeling, data foundations, and code review/cleanup Identify the data needed for a business problem and implement logging required to ensure availability of data, while working with data infrastructure to triage issues and resolve Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights in a meaningful way Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership Design, build and launch new data models and visualizations in production, leveraging common development toolkits Independently design, build and launch new data extraction, transformation and loading processes in production, mentoring others around efficient queries Support existing processes running in production and implement optimized solutions with limited guidance  Your Expertise:  Bachelor’s Degree preferred, or equivalent combination of education, training, and experience.  5+ years of professional experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.) 3+ years of professional experience with Enterprise Domains Like HR, Finance, Supply Chain 6+ years of professional experience with more than one SQL and relational databases including expertise in Presto, Spark, and MySQL  Professional experience designing and implementing real-time pipelines (Apache Kafka, or similar technologies) 5+ years of professional experience in custom ETL design, implementation, and maintenance 3+ years of professional experience with Data Modeling including expertise in Data Warehouse design and Dimensional Modeling  5+ years of professional experience working with cloud or on-premises Big Data/MPP analytics platform (Teradata, AWS Redshift, Google BigQuery, Azure Synapse Analytics, or similar) Experience with data quality and validation (using Apache Airflow) Experience with anomaly/outlier detection Experience with Data Science workflow (Jupyter Notebooks, Bento, or similar tools) Experience with Airflow or similar workflow management systems Experience querying massive datasets using Spark, Presto, Hive, or similar Experience building systems integrations, tooling interfaces, implementing integrations for ERP systems (Oracle, SAP, Salesforce, etc.)  Experience in data visualizations using Power BI and Tableau. Proficiency in Python programming language and Python libraries, with a focus on data engineering and data science applications. Professional fluency in English required   Applied Value is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information. Hiring is contingent on candidate verifying their eligibility to work in the United States and passing a complete background check.