Data Engineer

San Francisco, California
Current Date Script
Job ID:
Client Company:


-          8+ years of SQL (Oracle, AWS Redshift, Hive, etc.) experience is required

-          8+ years of experience with schema design and dimensional data modeling.

o   Ability to analyze data to identify deliverables, gaps and inconsistencies.

-          5+ years of Python or Ruby development experience is necessary; Python preferred but open to other languages

-          Strong experience working on Unix platform – Ubuntu preferred but open to other flavors

-          Ability in managing and communicating data warehouse plans to internal clients.

-          Experience designing, building and maintaining data processing systems

-          Experience working with visualization tools like Tableau or Micro Strategy



-          No-SQL experience is a plus

-          Experience in custom or structured (ie. Informatica /Talend /Pentaho) ETL design, implementation and maintenance;

-          Experience working with either a Map Reduce or a MPP system on any size/scale


Role Description – Day to Day Responsibilities

The Data Engineer is responsible for designing and developing robust, scalable solutions for collecting, analyzing large data sets, creating and maintaining data pipelines, data structures and reports to be used by the revenue organization at the SAAS company. These individuals will be compiling all of the Marketing and Financial data sets that they collect from their online traffic. For example, data will be pulled to see how much traffic actually ends up buying memberships to their software vs. how many hit the website and don’t continue with a purchase. There will also be Operational components, in which the engineer will look into over 100 data pipelines and make sure those are running up to standards. There will also be project based work, in which you will look for issues in data sources and processes. Below are some day to day tasks these resources will be responsible for:

·       Design, build and manage data marts to satisfy our growing data needs.

·       Understand business processes, applications and how data is gathered; and tie application telemetry to transactional data model.

·       Develop and manage data pipelines at enterprise scale

·       Build data expertise and own data quality for various data flows

·       Launch and support new data models that provide intuitive analytics to internal customers

·       Design and develop new framework and automation tools to enable teams to consume and understand data faster

·       Use your expert coding skills across a number of languages like SQL, Python and Java to support analysts and data scientists

·       Interface with internal data consumers to understand data needs

·       Collaborate with multiple teams in high visibility roles and own the solution end-to-end

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