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Because of just how big “The Cloud” is, I am trying to narrow our job searches a little. So this week we will focus on some particularly promising AWS Big Data positions from around the world.
First, though, let’s try and pin down exactly what Big Data is. The following excerpt is from the official AWS whitepaper Big Data Analytics Options on AWS and should give an idea.
As we become a more digital society the amount of data being created and collected is accelerating significantly. The analysis of this ever-growing data set becomes a challenge using traditional analytical tools. Innovation is required to bridge the gap between the amount of data that is being generated and the amount of data that can be analyzed effectively. Big data tools and technologies offer ways to efficiently analyze data to better understand customer preferences, to gain a competitive advantage in the marketplace, and to use as a lever to grow your business. The AWS ecosystem of analytical solutions is specifically designed to handle this growing amount of data and provide insight into ways your business can collect and analyze it.
1. Lead Quality Engineer (Big Data/Analytics, AWS, Scale)
TuneIn – San Francisco SOMA District
As a key member of the Quality Engineering team, you will work directly with business stakeholders to lead and execute a variety of projects on our streaming audio platform and big data services.
You will hold responsibility for full life-cycle management, including requirements analysis, test case planning and design, and execution of manual and automated tests and procedures. You will work side by side the engineering team and coordinate the efforts of testers onsite and out of the house.
- Identify overall QA milestones, dependencies, issues, risks, etc. for a specific project. Plan and coordinate QA activity accordingly.
- Define test methods and create test documentation for new or existing projects to ensure necessary test coverage
- Create test tools that will help test platform components and data flow through the system
- Maintain effective communication with development, PM and business stakeholders regarding project status and risk assessment.
- Work with and lead the offshore team.
2. Software Development Engineer – Big Data, AWS Elastic MapReduce (EMR)
Amazon – US-WA-Seattle
Want to change the world with Big Data and Analytics? Come join us on the Amazon Web services (AWS) Elastic MapReduce (EMR) team!
EMR is a massively scaled distributed service that gives users fast and predictable Big Data performance with clusters running Hadoop, Hive, Pig, Impala, Spark, Shark and more, with the ability to effortlessly scale up and down as needed. We run millions of customer clusters, enabling processing on vast datasets.
- Keeping your finger on the pulse of the constantly evolving and growing Big Data field
- Translation of complex functional and technical requirements into detailed architecture and design
- Delivering systems and features with top-notch quality, on time
- Stay current on technical knowledge to keep pace with rapidly changing technology, and work with the team in bringing new technologies on board
3. Big Data Engineer – SQL / ETL / AWS / Linux / SAP HANA
Burns Sheehan – London, United Kingdom
If you are a talented, passionate Big Data Engineer then an exciting new role has been created just for you! You’ll join a super impressive Data Analytics Team and play a key role on a number of very high profile projects in state of the art offices offering stunning views of London, an on-site gym and cool chill out area.
- Maintain and scale their data pipeline in the face of explosive growth
- Own one of many continuous improvement projects to expand the capacity and performance of their platform
- Support Data Analytics implementation of new tools to increase the robustness of our end-to-end data chain
- Develop tools for the administration and monitoring of their core data platform
Radley Group – Sydney, Australia
The benefits for the successful candidate will be:
- Silicon Valley style employee share schemes.
- Young, dynamic team at the forefront of their industry
- Tech. start up culture and environment
- Significant amount of support from SME’s in the business and an opportunity to hit the ground running and make this their own.
- a strong developer with at least 3 years experience in similar roles
- a core member of our engineering team
- concentrating on the improvement and expansion of our API
- working on our Angular client apps when needed
- taking ownership of automating and containerising our hosting
- prototyping new approaches and testing ideas
- helping to build an awesome engineering culture
5. Data Engineer – Visualization & Reporting
Babbel – Berlin, DE
We are looking for a Data Engineer (full-time) to start immediately in our office in Berlin-Kreuzberg, Germany.
With millions of regular users and more than 7000 hours of premium content, Babbel.com is growing fast while shaping the future of learning.
You are an experienced software engineer who has built and run cloud-based analytics infrastructure in internet companies before and you want to apply your expertise in the challenging setting of a fast-moving company.
In your role, you will help to evolve our existing data architecture and infrastructure to further enable data-driven insight.
You will collaborate closely with the technical product owner for Analytics, lead technical architects and the Analytics team to deliver analytics solutions for different stakeholders as well as introduce new technologies in the area of analytics, reporting, monitoring and dashboards, and Big Data.
- Manage reporting/dashboard plans for our different internal customers (e.g. product teams, marketing, finance, operations)
- Interface with engineers, analysts and managers to understand data needs.
- Design, develop, test, launch new reports and dashboards into production.
- Provide support to reports and dashboards running in production.
- Define and manage SLA for all data sets in allocated areas of ownership.
- Work with data architecture to triage infrastructure issues and drive to resolution.
- Build data expertise and own data quality in allocated areas of ownership.