senior engineer
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et's Dive In:
The Manager of Data Engineering supports report/dashboard development, the BI Semantic Layer, and Ad-Hoc analysis.
You are right for the job if you can:
- Develop BI Subject Areas and all associated objects with BI Tools (OBIEE or Tableau).
- Provide expert advice in the usage and interpretation of data.
- Develop reports and dashboards for both operational and analytic needs.
- Develop SQL scripts to extract complex data as necessary when not supported directly by BI tools.
- Create advanced visualizations leveraging tools (Tableau) or open source technology to effectively tell the story based on the underlying data.
- Develop real-time and batch data integration mappings.
- Process, clean, archive and monitor all data movement.
- Transition application processes to distributed processing framework.
- Engineer distributed services and front end Application Programming Interfaces (APIs) and tools for other developers to consume.
Skills and Experience:
- Master’s degree in Computer Science or related field or equivalent combination of industry related professional experience and education.
- 6-8 years providing technical guidance and oversight.
- Working experience in BI tools, such as OBIEE or Tableau.
- Working experience in multiple data analytics tools and systems.
- Working experience working with data structures.
- Working knowledge of data extrapolation, interpretation and chart compilation.
- Working knowledge of creating visualizations that effectively tell a story of the data.
- Working experience with Data Integration Tools, such as Informatica, Talend, SSIS.
- Working experience with Hadoop ecosystem technologies such as Hive, Pig, Spark.
- Working experience with distributed scalable data stores such as Hbase, Accumulo, BigTable, Redshift.
- Working experience with MapReduce-based frameworks.
- Working experience in design, development, and implementation of highly scalable, high-volume software systems and components, client-facing web applications, and major Internet-oriented applications and systems.
- Working experience working with high volume heterogeneous data, preferably with distributed systems such as Hadoop.
- Working experience with batch and real-time data processing frameworks.
- Working experience with data modeling, data access, and data storage techniques.
- Working experience working with relational and NoSQL databases.
- Working experience with business intelligence tools and platforms.
- Working experience with data quality tools.
- Working experience with application lifecycle methodologies (e.g. agile, iterative).
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