Data Engineer

Role : Software Engineer - Data Location - Austin TX Apple exp is preferred. We are seeking a highly experienced Engineer to join our team and own the development of a Tiered data architecture for our data. In this role, they would be responsible for crafting and building a comprehensive data architecture that will enable seamless data integration and enable the delivery of high-quality insights to our leadership and business stakeholders. Skills Required : Apache Spark, SQL, git, Programing Language (Python, Java, Scala) Nice to have : Understanding of Design Patterns, Able to discuss tradeoffs between RDBMS vs Distributed Storage Key Qualifications - Proven experience in data engineering, data architecture, or a related field - Experience in building and deploying tiered data architecture for analytics data is a plus - Strong understanding of data modeling, data warehousing, and ETL concepts - Proficiency in SQL and experience with at least one major data analytics platform, such as Hadoop or Spark - Experience with data orchestration tools like Airflow is a nice to have - Excellent problem-solving and analytical skills, and the ability to work well under tight deadlines - Excellent interpersonal skills and the ability to collaborate effectively with cross-functional teams Description - Design and implement a tiered data architecture that integrates analytics data from multiple sources in an efficient and effective manner. - Develop data models and mapping rules to transform raw data into actionable insights and reports. - Collaborate with the analytics and business teams to understand their requirements and deliver solutions that meet their needs. - Ensure data quality and accuracy by developing data validation and reconciliation processes. - Play an active role in the development and maintenance of user documentation, including data models, mapping rules, and data dictionaries. - Collaborate with multi-functional teams to define and implement data governance policies and standards. - Stay informed about the latest developments in data analytics and data management technologies and recommend new tools and methodologies to improve the semantic layer.