Big Data Solution Architect (post-sales) - Spark - Secret (or higher)

Location: Tysons, VA
Date Posted: 03-26-2019
This is a very cool company - become a Spark Analytics expert, work with the best and brightest, make a lot of money, get equity that is expected to be very valuable in a short amount of time, and work on some of the best federal analytics projects. Some details are listed below.

Our client is a product and services firm, pre-IPO, that specializes in data science and analytics for the federal government and commercial market. They utilize Apache Spark as the foundation of their products and solutions. This is NOT a sales role - it is a client-facing technical / engineering role. In addition to hands-on technical implementation work, you will consult on architecture and design of projects that are of strategic importance to Intelligence & Defense agencies.

This role is NOT dependent on contract funding - our client has numerous engagements that utilize their products and services, and when they find the right people, they make firm offers without customer interviews being required.

In this role, you will support their clients throughout the DC metro area. Local travel to customer sites will be as needed. On some projects, a large portion of the work can be done remotely, with only occasional in-person meetings with the customer.

To be considered for this role, you need the following:
- US citizenship and a current Secret clearance or higher.
- Strong experience in the Hadoop and/or Spark ecosystem
- Hands-on coding experience with Scala, Python, or Java

Hands-on Spark coding experience is a big plus, but not strictly required if your Hadoop and Scala / Python / Java experience is strong.

Good client-facing skills (consulting, verbal and written communication, etc.) are also important in this role.

In terms of compensation, you can expect a strong salary, a significant bonus opportunity, a full benefits plan, and equity (which can lead to substantial additional compensation).

cjobs-cat:"IT - Software"

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