About the function
In order to be a successful Technical Lead at Accenture, you’ll need to be comfortable guiding and mentoring a team of engineers and dealing with both internal and external stakeholders. You will be responsible for a team tasked with managing, transforming and cleansing high volume data, helping our Tier 1 clients solve business problems in the area of fraud, compliance and financial crime. We’re looking for hands-on technical leaders who are comfortable splitting their time between coding and managing the engineering team.
Being Agile is an integral part to the success we have at Accenture and leading regular team sprints and Scrum meetings with your engineering team is essential. You’ll be working closely with Data Scientists, Business Analysts, Technical Leads, Project Managers and Solutions Architects, with everyone following the same goal of meeting our clients expectations and delivering a first-class service.
We want our employees to use the latest and leading open source big-data technology possible. You will be using tools such as Spark, Hadoop, Scala, Data Fusion and Elasticsearch, with our platform being hosted on both private and public virtual clouds, such as Google cloud, Microsoft Azure and Amazon. Our primary language is written in Scala, but don’t worry If that’s not currently your strongest language, we make sure that every employees goes through our training academy so they’re comfortable and confident with using our platform.
Key Responsibilities:
- Leading a team and mentoring junior engineers.
- Guiding team members through technical issues and challenges.
- Ensuring that engineers are following best practices and standards.
- Leading SCRUM ceremonies and fostering a collaborative and fun working environment that values high performance and continuous improvement.
- Write defensive, fault tolerant and efficient code for data processing.
- Automate data processing to enable on-going alerts on high-risk activity.
- Participate in customer workshops and refinement sessions, presenting project results to clients both face to face and virtually.
- Work very closely with data scientists to ensure efficient and effective delivery of solutions.
- Use leading open source big-data tools, such as Spark, Hadoop, Scala and Elasticsearch. You should be comfortable with working with high profile clients, including on their sites.
- Work with our expert software development team to produce reusable applications.
- Use emerging and open-source technologies such as Spark, Hadoop, and Scala.
- Collaborate on scalability issues involving access to massive amounts of data and information.
- Take on ad-hoc tasks as required for the running of a small, yet rapidly expanding business.
Requirements:
- Must have: Quantexa Data Engineer Academy certification.
- Good time management and prioritizations skills to balance engineering, team management and customer facing responsibilities.
- Good communication skills and experience working with different customers, partner organisations and cultures.
- Proven big data experience, either from an implementation or a data science prospective.
- Have an excellent appreciation of what makes a high quality, operationally stable system and how to streamline all areas of development, release, and operations to achieve this.
- Arrive with experience at working with a variety of modern development tooling (e.g. Git, Gradle, Jenkins, Nexus) as well as technologies supporting automation and DevOps (e.g. Ansible, Chef, Puppet, Docker and a little bit of good old Bash scripting).
- Excellent technical skills including hands-on knowledge of at least one big data technology such as Spark, Hadoop, or Elasticsearch.
- Experience with MVC frameworks such as AngularJS
- Experience of building data processing pipelines for use in production “hands off” batch systems, including either (or preferably both) traditional ETL pipelines and/or analytics pipelines.
- Strong coding experience in the likes of Scala, Java, or Python.
- Enthusiasm to learn and develop emerging technologies and techniques.
- Exhibit strong technical communication skills with demonstrable experience of working in rapidly changing client environments.
- Demonstrate strong analytical and problem-solving skills and the ability to debug and solve technical challenges with sometimes unfamiliar technologies.
- Strong academic qualifications and come from a software engineering background or other scientific degree incorporating IT modules (e.g. Maths/Physics).
