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The Senior Data Warehouse Engineer will help architect, build, and maintain a robust, scalable, and sustainable business intelligence platform. Surrounded by a diverse group of fun and dedicated individuals, this role will tackle highly scalable systems with complex data models, heterogeneous ETL technologies, and large volumes of internet log and transactional data. This is a highly visible and strategic role as our business decisions are driven by data. As we grow, it will become even more important that we have the right data to make the right decisions. As the Sr. Data Warehouse Engineer, you are responsible for analysis, design, requirements gathering, functional/technical specification, development, deployment, and testing work related to the data warehouse. Essential Responsibilities • Design, develop, and maintain highly scalable ETL & Data Warehousing-related systems that use a variety of technologies to aggregate data from across various external entities and from within the business. • Engineer data warehousing solutions through the use of multiple technologies including: DBMS (Oracle, SQL Server, MySQL), App Dev (Java, Ruby, C++ etc), ETL tools (Informatica, Ab Initio, SSIS), OS (Solaris, HP-UX, Windows, Linux), scripting (Shell, Python, Perl).
• Integrate third party data into our enterprise data warehouse. Create and maintain the logical and physical dimensional data model. • Provide data streams from front-end/third-party systems to drive real-time business metrics and decisions • Invest time and effort to constantly learn latest technologies related to BI and big data applications. • Document business requirements, design specifications, and ETL operational manuals. • Join forces with analysts and stakeholders to gather, understand, and develop technical requirements • Recommend standards and methodology for creation, capture, maintenance, and integration of metadata • Provide expertise and leadership on making technical decisions, thus delivering a platform that provides business value and meets end user goals • Be flexible, adaptable, and available for full production support during off-business hours on a regular basis.
• Bachelor's degree in computer science, engineering, or information systems • 8+ years of experience in data warehousing (including dimensional modeling concepts) business requirements analysis, data-source analysis, data mapping, technical solution design, and database applications development with SQL databases. • 5+ years experience working as a developer in a Data Engineering, Data Warehousing / Business Intellegence team. • Comfortable in both a sole developer role as well as one of the members of a larger development team. • 5+ years of experience in data warehousing including data cleansing, optimization, high-volume (>2 terabytes – min 2 years), and near real-time ETL process design & development • Broad understanding of multiple technologies – including DBMS (Oracle, SQL Server, MySQL), Recent experience in application development (Java, Ruby, C++ etc), ETL tools (Informatica, Ab Initio, SSIS), OS (Solaris, HP-UX, Windows, Linux), scripting (Shell, Python, Perl). • Hands-on with at least 1 Big Data technology such as: Redshift, Hadoop, Candandra, Netezza, Mongo DB, etc. • Experience in integration with third party APIs • Interest in using cutting-edge technologies and modern languages to find new answers to old problems • Ability to learn new paradigms, tools, and processes quickly • Thrives in a fast-paced, rapidly-changing, exciting work environment • Ability to prioritize and work autonomously yet collaboratively when needed • Excellent communication skills and ability to convey ideas accurately and concisely to both technical and non-technical employees • Added advantage, if the candidate is experienced in some the following areas: • Open source data warehousing / business intelligence / ETL / big-data platforms & tools • Modern OLAP concepts and analytic tools, e.g., Tableau, ClikView, etc. • Experience with Amazon Redshift • Experience with emerging technologies such distributed file systems, document stores, and clustered databases (e.g. Hadoop, MapReduce, Greenplum, Vertica, Cassandra) • Data mining • Statistical analysis using R and related tools • Machine learning Required Skills • Ability to design, code, debug, and execute very large database solutions that meet specifications • Ability to gather and document specifications from monitoring business needs • Effective analytic and problem-solving skills to solve production problems very fast • Ability to prioritize and deal with conflicting demands • Strong verbal and written communication skills FYI Skills Requirements Absolute Requirements •
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